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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
$schema: string
$id: string
title: string
description: string
type: string
required: list<item: string>
child 0, item: string
additionalProperties: bool
properties: struct<id: struct<type: string, description: string>, dedup_key: struct<type: string, description: s (... 1555 chars omitted)
child 0, id: struct<type: string, description: string>
child 0, type: string
child 1, description: string
child 1, dedup_key: struct<type: string, description: string>
child 0, type: string
child 1, description: string
child 2, problem: struct<type: string, required: list<item: string>, additionalProperties: bool, properties: struct<te (... 199 chars omitted)
child 0, type: string
child 1, required: list<item: string>
child 0, item: string
child 2, additionalProperties: bool
child 3, properties: struct<text: struct<type: string>, tags: struct<type: string, items: struct<type: string>>, language (... 107 chars omitted)
child 0, text: struct<type: string>
child 0, type: string
child 1, tags: struct<type: string, items: struct<type: string>>
child 0, type: string
child 1, items: struct<type: string>
child 0, type: string
child 2, language: struct<type: list<item: string>>
child 0, type: list<item: string>
child 0, item: string
child 3, error_signature: struct<type: list<item: string>, description: s
...
e: list<item: string>
child 0, item: string
child 2, superseded_by: struct<type: list<item: string>>
child 0, type: list<item: string>
child 0, item: string
child 9, created_at: struct<type: string, format: string>
child 0, type: string
child 1, format: string
child 10, updated_at: struct<type: list<item: string>, format: string>
child 0, type: list<item: string>
child 0, item: string
child 1, format: string
problem: struct<text: string, tags: list<item: string>, language: string, error_signature: string>
child 0, text: string
child 1, tags: list<item: string>
child 0, item: string
child 2, language: string
child 3, error_signature: string
provenance: struct<source: string, solved_by_model: null, contributor: string, so_post_id: int64, license: strin (... 2 chars omitted)
child 0, source: string
child 1, solved_by_model: null
child 2, contributor: string
child 3, so_post_id: int64
child 4, license: string
score: int64
updated_at: null
dedup_key: string
outcome: struct<success_count: int64, failure_count: int64>
child 0, success_count: int64
child 1, failure_count: int64
id: string
version: struct<commit: null, supersedes: null, superseded_by: null>
child 0, commit: null
child 1, supersedes: null
child 2, superseded_by: null
created_at: string
tier: string
solution: struct<text: string, code: string>
child 0, text: string
child 1, code: string
to
{'id': Value('string'), 'problem': {'text': Value('string'), 'tags': List(Value('string')), 'language': Value('string'), 'error_signature': Value('string')}, 'solution': {'text': Value('string'), 'code': Value('string')}, 'provenance': {'source': Value('string'), 'solved_by_model': Value('null'), 'contributor': Value('string'), 'so_post_id': Value('int64'), 'license': Value('string')}, 'outcome': {'success_count': Value('int64'), 'failure_count': Value('int64')}, 'version': {'commit': Value('null'), 'supersedes': Value('null'), 'superseded_by': Value('null')}, 'created_at': Value('string'), 'updated_at': Value('null'), 'dedup_key': Value('string'), 'score': Value('int64'), 'tier': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1816, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
$schema: string
$id: string
title: string
description: string
type: string
required: list<item: string>
child 0, item: string
additionalProperties: bool
properties: struct<id: struct<type: string, description: string>, dedup_key: struct<type: string, description: s (... 1555 chars omitted)
child 0, id: struct<type: string, description: string>
child 0, type: string
child 1, description: string
child 1, dedup_key: struct<type: string, description: string>
child 0, type: string
child 1, description: string
child 2, problem: struct<type: string, required: list<item: string>, additionalProperties: bool, properties: struct<te (... 199 chars omitted)
child 0, type: string
child 1, required: list<item: string>
child 0, item: string
child 2, additionalProperties: bool
child 3, properties: struct<text: struct<type: string>, tags: struct<type: string, items: struct<type: string>>, language (... 107 chars omitted)
child 0, text: struct<type: string>
child 0, type: string
child 1, tags: struct<type: string, items: struct<type: string>>
child 0, type: string
child 1, items: struct<type: string>
child 0, type: string
child 2, language: struct<type: list<item: string>>
child 0, type: list<item: string>
child 0, item: string
child 3, error_signature: struct<type: list<item: string>, description: s
...
e: list<item: string>
child 0, item: string
child 2, superseded_by: struct<type: list<item: string>>
child 0, type: list<item: string>
child 0, item: string
child 9, created_at: struct<type: string, format: string>
child 0, type: string
child 1, format: string
child 10, updated_at: struct<type: list<item: string>, format: string>
child 0, type: list<item: string>
child 0, item: string
child 1, format: string
problem: struct<text: string, tags: list<item: string>, language: string, error_signature: string>
child 0, text: string
child 1, tags: list<item: string>
child 0, item: string
child 2, language: string
child 3, error_signature: string
provenance: struct<source: string, solved_by_model: null, contributor: string, so_post_id: int64, license: strin (... 2 chars omitted)
child 0, source: string
child 1, solved_by_model: null
child 2, contributor: string
child 3, so_post_id: int64
child 4, license: string
score: int64
updated_at: null
dedup_key: string
outcome: struct<success_count: int64, failure_count: int64>
child 0, success_count: int64
child 1, failure_count: int64
id: string
version: struct<commit: null, supersedes: null, superseded_by: null>
child 0, commit: null
child 1, supersedes: null
child 2, superseded_by: null
created_at: string
tier: string
solution: struct<text: string, code: string>
child 0, text: string
child 1, code: string
to
{'id': Value('string'), 'problem': {'text': Value('string'), 'tags': List(Value('string')), 'language': Value('string'), 'error_signature': Value('string')}, 'solution': {'text': Value('string'), 'code': Value('string')}, 'provenance': {'source': Value('string'), 'solved_by_model': Value('null'), 'contributor': Value('string'), 'so_post_id': Value('int64'), 'license': Value('string')}, 'outcome': {'success_count': Value('int64'), 'failure_count': Value('int64')}, 'version': {'commit': Value('null'), 'supersedes': Value('null'), 'superseded_by': Value('null')}, 'created_at': Value('string'), 'updated_at': Value('null'), 'dedup_key': Value('string'), 'score': Value('int64'), 'tier': Value('string')}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
id string | problem dict | solution dict | provenance dict | outcome dict | version dict | created_at string | updated_at null | dedup_key string | score int64 | tier string |
|---|---|---|---|---|---|---|---|---|---|---|
seed-0001 | {
"text": "Python requests raises SSLError CERTIFICATE_VERIFY_FAILED when calling an HTTPS API on a fresh machine, even though the URL opens fine in a browser.",
"tags": [
"python",
"requests",
"ssl",
"tls"
],
"language": "python",
"error_signature": "requests.exceptions.SSLError: CERTIFICATE_... | {
"text": "The Python trust store is missing CA certificates. Upgrade certifi and point requests at it; on macOS python.org builds also run the bundled 'Install Certificates.command'. Then verify with a direct request.",
"code": "pip install --upgrade certifi\nimport requests, certifi\nrequests.get('https://api.git... | {
"source": "human",
"solved_by_model": null,
"contributor": "seed",
"so_post_id": null,
"license": null
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T12:59:17.656748+00:00 | null | cb6df520450b2fe3146091bd70d7d3596b69f6a9911782d6480df680bf3ad40a | 8 | high |
so-1 | {
"text": "What is \"backprop\"?\n\nWhat does \"backprop\" mean? Is the \"backprop\" term basically the same as \"backpropagation\" or does it have a different meaning?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "\"Backprop\" is the same as \"backpropagation\": it's just a shorter way to say it. It is sometimes abbreviated as \"BP\".",
"code": null
} | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 1,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | 3432e33a3694114bfde449b72fd4c57e3984343fa99c598f2ea8db56ff0fbc65 | 8 | high |
so-2 | {
"text": "How does noise affect generalization?\n\nDoes increasing the noise in data help to improve the learning ability of a network? Does it make any difference or does it depend on the problem being solved? How is it affect the generalization process overall?",
"tags": [],
"language": null,
"error_signatur... | {
"text": "Noise in the data, to a reasonable amount, may help the network to generalize better. Sometimes, it has the opposite effect. It partly depends on the kind of noise (\"true\" vs. artificial).\n\nThe AI FAQ on ANN gives a good overview. Excerpt:\n\n\n Noise in the actual data is never a good thing, since it... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 2,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | fc1eb727e634432aee22f362bd7091b91b545af2f2c9323137cf2966cd4fad3c | 7 | medium |
so-4 | {
"text": "How to find the optimal number of neurons per layer?\n\nWhen you're writing your algorithm, how do you know how many neurons you need per single layer? Are there any methods for finding the optimal number of them, or is it a rule of thumb?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "There is no direct way to find the optimal number of them: people empirically try and see (e.g., using cross-validation). The most common search techniques are random, manual, and grid searches. \n\nThere exist more advanced techniques such as Gaussian processes, e.g. Optimizing Neural Network Hyperparamet... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 4,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | 40dc515a26b75e23da6407bd0b6d376f345052d0f90b4ce5c6661a82f546a531 | 8 | high |
so-7 | {
"text": "Why does Stephen Hawking say \"Artificial Intelligence will kill us all\"?\n\nThis quote by Stephen Hawking has been in headlines for quite some time:\n\nArtificial Intelligence could wipe out humanity when it gets too clever as humans will be like ants.\n\nWhy does he say this? To put it simply: what are ... | {
"text": "It's not just Hawking, you hear variations on this refrain from a lot of people. And given that they're mostly very smart, well educated, well informed people (Elon Musk is another, for example), it probably shouldn't be dismissed out of hand.\n\nAnyway, the basic idea seems to be this: If we create \"rea... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 7,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | f63f4f92ed336b7162beffa8772cd8d9a774eb80e710cc85583b3027d0582e37 | 6 | medium |
so-6 | {
"text": "Are humans intelligent according to the definition of an intelligent agent?\n\nGiven the following definition of an intelligent agent (taken from a Wikipedia article)\n\n\n If an agent acts so as to maximize the expected value of a performance measure based on past experience and knowledge then it is inte... | {
"text": "It rather depends on how one defines several of the terms used. For example:\n\n\nWhether the term \"expected\" is interpreted in a formal (i.e.\nstatistical) sense. \nWhether it's assumed that humans have any kind of utilitarian\n\"performance measure\".\n\n\nThe motivation for this description of \"agen... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 6,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | 0a1eed141ab1f79eb75557fe207b835d4ea3d60b9c93e1e596f5c60aa8b6db79 | 6 | medium |
so-15 | {
"text": "Is the Turing Test, or any of its variants, a reliable test of artificial intelligence?\n\nThe Turing Test was the first test of artificial intelligence and is now a bit outdated. The Total Turing Test aims to be a more modern test which requires a much more sophisticated system. What techniques can we use... | {
"text": "The rhetorical point of the Turing Test is that it places the 'test' for 'humanity' in observable outcomes, instead of in internal components. If you would behave the same in interacting with an AI as you would with a person, how could you know the difference between them?\n\nBut that doesn't mean it's rel... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 15,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | edb96344352593e2bf260fb49800d32cab87af867fe982ae40d6c2b5ad15d31f | 7 | medium |
so-10 | {
"text": "What is fuzzy logic?\n\nI'm new to A.I. and I'd like to know in simple words, what is the fuzzy logic concept? How does it help, and when is it used?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "As complexity rises, precise statements lose meaning and meaningful statements lose precision. ( Lofti Zadeh ).\n\nFuzzy logic deals with reasoning that is approximate rather than fixed and exact. This may make the reasoning more meaningful for a human:\n\n\n\n\n\nFuzzy logic is an extension of Boolean log... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 10,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | 133ee822ec6abffc18119a76383545f2b882a1792923a567f380951cac5b8385 | 9 | cinema |
so-17 | {
"text": "What is the concept of the technological singularity?\n\nI've heard the idea of the technological singularity, what is it and how does it relate to Artificial Intelligence? Is this the theoretical point where Artificial Intelligence machines have progressed to the point where they grow and learn on their o... | {
"text": "The technological singularity is a theoretical point in time at which a self-improving artificial general intelligence becomes able to understand and manipulate concepts outside of the human brain's range, that is, the moment when it can understand things humans, by biological design, can't.\nThe fuzziness... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 17,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | 1da08e19b9894c16b5a51e0960699bfd3383b367a618d71fb72da6b883332c84 | 9 | cinema |
so-28 | {
"text": "Is a genetic algorithm an example of artificial intelligence?\n\nSince human intelligence presumably is a function of a natural genetic algorithm in nature, is using a genetic algorithm in a computer an example of artificial intelligence? If not, how do they differ? Or perhaps some are and some are not exp... | {
"text": "An ability that is commonly attributed to intelligence is problem solving. \nAnother one is learning (improving itself from experience).\nArtificial intelligence can be defined as \"replicating intelligence, or parts of it, at least in appearance, inside a computer\" (dodging the definition of intelligence... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 28,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | 64889cc2d8c7b3d422209d861c561aed43b926c462cefb2f4205bb74b6abc07b | 8 | high |
so-40 | {
"text": "What is the \"dropout\" technique?\n\nWhat purpose does the \"dropout\" method serve and how does it improve the overall performance of the neural network?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "Dropout means that every individual data point is only used to fit a random subset of the neurons. This is done to make the neural network more like an ensemble model.\n\nThat is, just as a random forest is averaging together the results of many individual decision trees, you can see a neural network train... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 40,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | da4d2da4fa0eae0e480785b9084eb50bbb15c0d4387fbdb092107880a74be754 | 7 | medium |
so-42 | {
"text": "What is the purpose of the hidden layers?\n\nWhy would anybody want to use \"hidden layers\"? How do they enhance the learning ability of the network in comparison to the network which doesn't have them (linear models)?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "\"Hidden\" layers really aren't all that special... a hidden layer is really no more than any layer that isn't input or output. So even a very simple 3 layer NN has 1 hidden layer. So I think the question isn't really \"How do hidden layers help?\" as much as \"Why are deeper networks better?\". \n\nAnd t... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 42,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | c6765a65f2722f9db7381415e1c2423659cb431ab8499d0104256a9b69122d25 | 7 | medium |
so-35 | {
"text": "What is the difference between artificial intelligence and machine learning?\n\nThese two terms seem to be related, especially in their application in computer science and software engineering.\n\nIs one a subset of another?\nIs one a tool used to build a system for the other?\nWhat are their differences a... | {
"text": "Machine learning has been defined by many people in multiple (often similar) ways [1, 2]. One definition says that machine learning (ML) is the field of study that gives computers the ability to learn without being explicitly programmed.\nGiven the above definition, we might say that machine learning is ge... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 35,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | 935168d771be04b0f536a470b84bd784fb4c8c8355ee1fa4b31466643942eabc | 8 | high |
so-36 | {
"text": "To what extent can quantum computers help to develop Artificial Intelligence?\n\nWhat aspects of quantum computers, if any, can help to further develop Artificial Intelligence?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "Quantum computers are super awesome at matrix multiplication, with some limitations. Quantum superposition allows each bit to be in a lot more states than just zero or one, and quantum gates can fiddle those bits in many different ways. Because of that, a quantum computer can process a lot of information a... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 36,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | 353ea647653a31c7b6164f1db5fa18b30f008c55f65c969e38e7aae2a409758b | 9 | cinema |
so-41 | {
"text": "Can the IQ of an AI program be measured?\n\nCan an AI program have an IQ? In other words, can the IQ of an AI program be measured? Like how humans can do an IQ test.",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "Short answer: No.\n\nLonger answer: It depends on what IQ exactly is, and when the question is asked compared to ongoing development. The topic you're referring to is actually more commonly described as AGI, or Artificial General Intelligence, as opposed to AI, which could be any narrow problem solving cap... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 41,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
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so-58 | {
"text": "Who first coined the term Artificial Intelligence?\n\nWho first coined the term Artificial Intelligence? Is there a published research paper that first used that term?",
"tags": [],
"language": null,
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} | {
"text": "John McCarthy (1927 - 2011) was an American computer scientist. A pioneer in the foundations of artificial intelligence research, he coined the term \"artificial intelligence\". He was one of the creators of the (original) Lisp programming language, which was quite involved in early AI research in the 1960... | {
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so-54 | {
"text": "Does the recent advent of a Go playing computer represent Artificial Intelligence?\n\nI read that in the spring of 2016 a computer Go program was finally able to beat a professional human for the first time. \n\nNow that this milestone has been reached, does that represent a significant advance in artific... | {
"text": "There are at least two questions in your question: \n\n\n What are some of the methods used to program the successful go playing program?\n\n\nand\n\n\n Are those methods considered to be artificial intelligence?\n\n\nThe first question is deep and technical, the second broad and philosophical.\n\nThe me... | {
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so-46 | {
"text": "When did Artificial Intelligence research first start?\n\nWhen did research into Artificial Intelligence first begin? Was it called Artificial Intelligence then or was there another name?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "The earliest research into thinking machines was inspired by a confluence of ideas that became prevalent in the late 30s, 40s and early 50s (e.g. formal logic, automata, robots). Although the Turing test was proposed in the 1950s by Alan Turing, the work culminated back in the 1940s in the invention of the... | {
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so-67 | {
"text": "What are the real world uses for SAT solvers?\n\nWhy somebody would use SAT solvers (Boolean satisfiability problem) to solve their real world problems?\n\nAre there any examples of the real uses of this model?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "Instead of talking about just SAT solvers, let me talk about optimization in general. Many economic problems can be cast as optimization problems: for example, FedEx may have a list of packages and the destinations for those packages, and must decide which packages to put on which trucks, and what order to... | {
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so-37 | {
"text": "What is a Markov chain and how can it be used in creating artificial intelligence?\n\nI believe a Markov chain is a sequence of events where each subsequent event depends probabilistically on the current event. What are examples of the application of a Markov chain and can it be used to create artificial ... | {
"text": "A Markov model includes the probability of transitioning to each state considering the current state. \"Each state\" may be just one point - whether it rained on specific day, for instance - or it might look like multiple things - like a pair of words. You've probably seen automatically generated weird tex... | {
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so-75 | {
"text": "What's the state of the art w.r.t research on the legal aspects of Artificial Intelligence?\n\nAs AI gains capabilities, and becomes more prevalent in society, our legal system will encounter questions it has not encountered before. For example, if a self-driving car is involved in an accident while being... | {
"text": "One person working in this space is Dr. Woody Barfield. He just wrote a book titled Cyberhumans: Our Future With Machines that focuses largely on the legal/policy issues around AI (and related topics). In addition to the book, he is continuing with other research in this area.",
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so-80 | {
"text": "What are the specific requirements of the Turing test?\n\nWhat are the specific requirements of the Turing test? \n\n\nWhat requirements if any must the evaluator fulfill in order to be qualified to give the test?\nMust there always be two participants in the conversation (one human and one computer) or ca... | {
"text": "The \"Turing Test\" is generally taken to mean an updated version of the Imitation Game Alan Turing proposed in his 1951 paper of the same name. An early version had a human (male or female) and a computer, and a judge had to decide which is which, and what gender they were if human. If they were correct l... | {
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so-81 | {
"text": "What are some examples of Statistical AI applications?\n\nI believe that statistical AI uses inductive thought processes. For example, deducing a trend from a pattern, after training.\nWhat are some examples of successfully applied Statistical AI to real-world problems?",
"tags": [],
"language": null,
... | {
"text": "There are several examples. For example, one instance of using Statistical AI from my workplace is:\n\n\nAnalyzing the behavior of the customer and their food-ordering trends, and then trying to upsell by recommending them the dishes which they might like to order/eat. This can be done through the apriori ... | {
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so-84 | {
"text": "Are methods of exhaustive search considered to be AI?\n\nSome programs do exhaustive searches for a solution while others do heuristic searches for a similar answer. For example, in chess, the search for the best next move tends to be more exhaustive in nature whereas, in Go, the search for the best next m... | {
"text": "If one thinks of intelligence as a continuous measure of optimization power (that is, how much better are outcomes for any unit of cognitive effort expended), then exhaustive search has non-zero intelligence (in that it does actually give better outcomes as more effort is expended) but very, very low intel... | {
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so-86 | {
"text": "How is a deep neural network different from other neural networks?\n\nHow is a neural network having the \"deep\" adjective actually distinguished from other similar networks?",
"tags": [],
"language": null,
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} | {
"text": "The difference is mostly in the number of layers. \n\nFor a long time, it was believed that \"1-2 hidden layers are enough for most tasks\" and it was impractical to use more than that, because training neural networks can be very computationally demanding.\n\nNowadays, computers are capable of much more, ... | {
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so-91 | {
"text": "Are search engines considered AI?\n\nAre search engines considered AI because of the way they analyze what you search for and remember it? Or how they send you ads of what you've searched for recently? \n\nIs this considered AI or just smart?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "I believe it would be more accurate to say that (some) search engines use AI. Broadly saying \"search engines are AI\" is not really correct. At the core, most search engines are nothing more than an inverted text index using something like tf–idf scoring. That's a very mechanical/simple thing that nobody... | {
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so-96 | {
"text": "What is a deep neural network?\n\nWhat is the definition of a deep neural network? Why are they so popular or important?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "A deep neural network (DNN) is nothing but a neural network which has multiple layers, where multiple can be subjective.\n\nIMHO, any network which has 6 or 7 or more layers is considered deep. So, the above would form a very basic definition of a deep network.",
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so-103 | {
"text": "What are some examples of Classical AI applications?\n\nI believe that Classical AI uses deductive thought processes. For example, given as a set of constraints, deduce a conclusion.\nWhat are some examples of successfully applying Classical AI to real-world problems?",
"tags": [],
"language": null,
... | {
"text": "The term classical AI refers to the concept of intelligence that was broadly accepted after the Dartmouth Conference and basically refers to a kind of intelligence that is strongly symbolic and oriented to logic and language processing. One basic point is the duality body vs. mind. It's in this period that... | {
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so-108 | {
"text": "What are the main advantages of using declarative programming languages for building AI?\n\nWhat specific advantages of declarative languages make them more applicable to AI than imperative languages? \n\nWhat can declarative languages do easily that other languages styles find difficult for this kind of ... | {
"text": "The advantage of a declarative language like Prolog is that it can be used to express facts and inference rules separately from control flow. \n\nThis allows the developer to focus on the data and inference rules (the knowledge model), and allows the developer to extend the knowledge model more easily.\n\... | {
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so-104 | {
"text": "Can artificial intelligence be thought of as optimization?\n\nIn this video an expert says, \"One way of thinking about what intelligence is [specifically with regard to artificial intelligence], is as an optimization process.\"\n\nCan intelligence always be thought of as an optimization process, and can a... | {
"text": "A good answer to this question depends on what you want to use the labels for.\n\nWhen I think about \"optimization,\" I think about a solution space and a cost function; that is, there are many possible answers that could be returned and we can know what the cost is of any particular answer.\n\nIn this vi... | {
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so-113 | {
"text": "What's the difference between hyperbolic tangent and sigmoid neurons?\n\nTwo common activation functions used in deep learning are the hyperbolic tangent function and the sigmoid activation function. I understand that the hyperbolic tangent is just a rescaling and translation of the sigmoid function: \n\n$... | {
"text": "Sigmoid > Hyperbolic tangent:\n\nAs you mentioned, the application of Sigmoid might be more convenient than hyperbolic tangent in the cases that we need a probability value at the output (as @matthew-graves says, we can fix this with a simple mapping/calibration step). In other layers, this makes no sense.... | {
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so-118 | {
"text": "How can fuzzy logic be used in creating AI?\n\nFuzzy logic is the logic where every statement can have any real truth value between 0 and 1.\n\nHow can fuzzy logic be used in creating AI? Is it useful for certain decision problems involving multiple inputs? Can you give an example of an AI that uses it?",
... | {
"text": "A classical example of fuzzy logic in an AI is the expert system Mycin.\n\nFuzzy logic can be used to deal with probabilities and uncertainties. \n\nIf one looks at, for example, predicate logic, then every statement is either true or false. In reality, we don't have this mathematical certainty. \n\nFor ex... | {
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so-120 | {
"text": "How does Lucas's argument work?\n\nIn Minds, Machines and Gödel (1959), J. R. Lucas shows that any human mathematician can not be represented by an algorithmic automaton (a Turing Machine, but any computer is equivalent to it by the Church-Turing thesis), using Gödel's incompleteness theorem.\nAs I underst... | {
"text": "Yes, it applies. If a statement cannot be derived in a finite number of steps, then it doesn't matter if the person trying to prove it is a human or a computer. \n\nThe mathematician has one advantage over a standard theorem proving algorithm: the mathematician can \"step out of the system\" (as Douglas H... | {
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so-123 | {
"text": "Does the Chinese Room argument hold against AI?\n\nBack in college, I had a Complexity Theory teacher who stated that artificial intelligence was a contradiction in terms. If it could be calculated mechanically, he argued, it wasn't intelligence, it was math.\n\nThis seems to be a variant of the Chinese Ro... | {
"text": "It depends on the definition of (artificial) intelligence.\nThe position that Searle originally tried to refute with the Chinese room experiment was the so-called position of strong AI: An appropriately programmed computer would have a mind in the exact same sense as humans have minds.\nAlan Turing tried t... | {
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so-77 | {
"text": "Is Lisp still being used to tackle AI problems?\n\nI know that language of Lisp was used early on when working on artificial intelligence problems. Is it still being used today for significant work? If not, is there a new language that has taken its place as the most common one being used for work in AI to... | {
"text": "Overall, the answer is no, but the current paradigms owe a lot to LISP. The language most commonly used today is python.\n\nRelevant answers:\n\n\nStack Overflow thread explaining why LISP was thought of as the AI language: Why is Lisp used for AI\nQuora answer by Peter Norvig, who wrote a popular textbook... | {
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so-94 | {
"text": "What is the significance of weights in a feedforward neural network?\n\nIn a feedforward neural network, the inputs are fed directly to the outputs via a series of weights.\nWhat purpose do the weights serve, and how are they significant in this neural network?",
"tags": [],
"language": null,
"error_... | {
"text": "You described a single-layer feedforward network. They can have multiple layers. The significance of the weights is that they make a linear transformation from the output of the previous layer and hand it to the node they are going to. To say it more simplistically, they specify how important (and in what ... | {
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so-111 | {
"text": "How could self-driving cars make ethical decisions about who to kill?\n\nObviously, self-driving cars aren't perfect, so imagine that the Google car (as an example) got into a difficult situation.\nHere are a few examples of unfortunate situations caused by a set of events:\n\nThe car is heading toward a c... | {
"text": "How could self-driving cars make ethical decisions about who to kill?\n\n\nIt shouldn't. Self-driving cars are not moral agents. Cars fail in predictable ways. Horses fail in predictable ways. \n\n\n the car is heading toward a crowd of 10 people crossing the road, so\n it cannot stop in time, but it can... | {
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so-130 | {
"text": "What are the main differences between a deep Boltzmann machine and a deep belief network?\n\nWhat are the main differences between a deep Boltzmann machine (DBM) (a recurrent neural network) and a deep belief network (which is based on RBMs)?",
"tags": [],
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} | {
"text": "The graph that represents a deep Boltzmann machine can be any weighted undirected graph. \n\nHowever, the graph that represents a deep Belief network must be a connection of graphs that represent restricted Boltzmann machines. Those graphs are bipartite, so there are two groups of vertices in those graphs ... | {
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so-50 | {
"text": "How can the generalization error be estimated?\n\nHow would you estimate the generalization error? What are the methods of achieving this?",
"tags": [],
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} | {
"text": "Generalization error is the error obtained by applying a model to data it has not seen before. So, if you want to measure generalization error, you need to remove a subset from your data and don't train your model on it. After training, you verify your model accuracy (or other performance measures) on the ... | {
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so-74 | {
"text": "What is the difference between strong-AI and weak-AI?\n\nI've heard the terms strong-AI and weak-AI used. Are these well defined terms or subjective ones? How are they generally defined?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "The terms strong and weak don't actually refer to processing, or optimization power, or any interpretation leading to \"strong AI\" being stronger than \"weak AI\". It holds conveniently in practice, but the terms come from elsewhere. In 1980, John Searle coined the following statements:\n\n\nAI hypothesis... | {
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so-16 | {
"text": "What is \"early stopping\" in machine learning?\n\nWhat is early stopping in machine learning and, in general, artificial intelligence? What are the advantages of using this method? How does it help exactly?\n\nI'd be interested in perspectives and links to recent research.",
"tags": [],
"language": nu... | {
"text": "In some iterative learning methods the more iterations you apply the more specific your model becomes about the training set. If there are too many iterations, your model will become too specifically trained for the training samples and will score less on other samples that are not seen during the training... | {
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so-140 | {
"text": "Does this argument refuting the existence of superintelligence work?\n\nA superintelligence is a machine that can surpass all intellectual activities by any human, and such a machine is often portrayed in science fiction as a machine that brings mankind to an end.\n\nAny machine is executed using an algori... | {
"text": "I believe this argument is based on the fact that intelligence is a single dimension when it really isn't. Are machines and humans really on the same level if a machine can solve a complex problem in a millionth of the time a human can? \n\nIt also assumes that the Turing machine is still the best computat... | {
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so-154 | {
"text": "Is it possible to train the neural network to solve math equations?\n\nI'm aware that neural networks are probably not designed to do that, however asking hypothetically, is it possible to train the deep neural network (or similar) to solve math equations?\n\nSo given the 3 inputs: 1st number, operator sig... | {
"text": "Yes, it has been done!\nHowever, the applications aren't to replace calculators or anything like that. The lab I'm associated with develops neural network models of equational reasoning to better understand how humans might solve these problems. This is a part of the field known as Mathematical Cognition. ... | {
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so-13 | {
"text": "Can a single neural network handle recognizing two types of objects, or should it be split into two smaller networks?\n\nIn particular, an embedded computer (with limited resources) analyzes live video stream from a traffic camera, trying to pick good frames that contain license plate numbers of passing ca... | {
"text": "Well, I do not know what type of features you are giving to your neural network. However, in general, I would go with a single neural network. It seems that you have no limitation in resources for training your network and the only problem is resources while you apply your network. \n\nThe thing is that pr... | {
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so-148 | {
"text": "What limits, if any, does the halting problem put on Artificial Intelligence?\n\nGiven the proven halting problem for Turing machines, can we infer limits on the ability of strong Artificial Intelligence?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "Does the halting problem imply any limits on human cognition?\n\nYes, absolutely--that there are pieces of code a human could look at and not be sure whether or not it will halt in finite time. (Certainly there are pieces of code that a human can look at and say \"yes\" or \"no\" definitely, but we're talk... | {
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so-167 | {
"text": "Why would neural network dream scenes mirror the hallucinations people experience when they're tripping?\n\nIn DeepDream wikipedia page it's suggested that a dreamlike images created by a convolutional neural network may be related to how visual cortex works in humans when they're tripping.\n\n\n The imag... | {
"text": "The similarity of artificial neural networks and the human visual cortex goes very deep, and in many ways the human visual cortex was the inspiration for the techniques we use for the design and implementation of ANNs designed for image recognition. So in that direction, the similarity seems obvious to me.... | {
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so-169 | {
"text": "What are the challenges for recognising the handwritten characters?\n\nThis 2014 article saying that a Chinese team of physicists have trained a quantum computer to recognise handwritten characters.\n\nWhy did they have to use a quantum computer to do that?\n\nIs it just for fun and demonstration, or is it... | {
"text": "Handwritten digit recognition is a standard benchmark in Machine Learning in the form of the MNIST dataset. For example, scikit-learn, a python package for Machine Learning uses it as a tutorial example. \n\nThe paper you cite uses this standard task as a proof of concept, to show that their system works."... | {
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so-26 | {
"text": "How could emotional intelligence be implemented?\n\nI've seen emotional intelligence defined as the capacity to be aware of, control, and express one's emotions, and to handle interpersonal relationships judiciously and empathetically. \n\n\nWhat are some strategies for artificial intelligence to begin to... | {
"text": "Architectures for recognizing and generating emotion are typically somewhat complex and don't generally have short descriptions, so it's probably better to reference the literature rather than give a misleading soundbite:\nSome of the early work in affective computing was done by Rosalind W. Picard. There ... | {
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so-172 | {
"text": "Could AIs self-develop in the future?\n\nIs it possible that, at some time in the future, AIs will be able to initiatively develop themselves, rather than passively being developed by humanity?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "This is known as the intelligence explosion hypothesis or recursive self-improvement.",
"code": null
} | {
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so-182 | {
"text": "How do I decide the optimal number of layers for a neural network?\n\nHow do I decide the optimal number of layers for a neural network (feedforward or recurrent)?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "There is a technique called Pruning in neural networks, which is used just for this same purpose.\n\nThe pruning is done on the number of hidden layers. The process is very similar to the pruning process of decision trees. The pruning process is done as follows:\n\n\nTrain a large, densely connected, netwo... | {
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so-184 | {
"text": "Are there emergent models of time in robots?\n\nI am interested in the emergence of properties in agents, and, more generally in robotics.\n\nI was wondering if there is work on the emergence of time-related concepts, on the low-level representation of notions like before and after. I know, for example, th... | {
"text": "To my knowledge, this is very much an open research issue.\n\nHere is a paper by Prof Leslie Smith, an acknowledged expert on neuromorphic perceptual coding, which explains the importance of the notion of perceptual time for Artificial General Intelligence and sketches an architecture from which a notion ... | {
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so-186 | {
"text": "Does a quantum computer resolve the halting problem and would that advance strong AI?\n\nHave there been proposed extensions to go beyond a Turing machine that solve the halting problem and if so, would those proposed extensions have value to advance strong Artificial Intelligence? For example, does quant... | {
"text": "It depends a bit on what you mean by 'quantum computer'. The 'conventional' notion is that quantum computation buys a (in some cases, exponential) speedup - it doesn't change what can be computed, just how quickly.\n\nIn contrast, advocates of hypercomputation claim that quantum effects may make it possibl... | {
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so-146 | {
"text": "In what ways can connectionist AI be integrated with GOFAI?\n\nIn what ways can connectionist artificial intelligence (neural networks) be integrated with Good Old-Fashioned A.I. (GOFAI)? For instance, how could deep neural networks be integrated with knowledge bases or logical inference? One such example ... | {
"text": "A neural net with even a single hidden layer is capable of Universal function approximation - it can approximate any continuous function 'as closely as you like'.\n\nHence, one option would be to look for GOFAI applications that would benefit from this property - for example, in state-space search approach... | {
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so-191 | {
"text": "What was the first machine that was able to carry on a conversation?\n\nWhat was the first AI that was able to carry on a conversation, with real responses, such as in the famous 'I am not a robot. I am a unicorn' case?\n\nA 'real response' constitutes a sort-of personalized answer to a specific input by a... | {
"text": "The well-known 'Eliza' program (Weizenbaum, ~1964) would appear to be the first. \n\nEliza was designed to model the emotionally-neutral response of a psychotherapist and this masks some of the weaknesses of its limited underlying pattern-matching mechanisms.",
"code": null
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so-70 | {
"text": "Is the pattern recognition capability of CNNs limited to image processing?\n\nCan a Convolutional Neural Network be used for pattern recognition in problem domains without image data? For example, by representing abstract data in an image-like format with spatial relations? Would that always be less effici... | {
"text": "Convolutional Nets (CNN) rely on mathematical convolution (e.g. 2D or 3D convolutions), which is commonly used for signal processing. Images are a type of signal, and convolution can equally be used on sound, vibrations, etc. So, in principle, CNNs can find applications to any signal, and probably more.\n\... | {
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so-202 | {
"text": "How can you simulate level of curiosity for a chatbot?\n\nI'd like to know more about implementing emotional intelligence.\nGiven I'm implementing a chatbot and I'd like to introduce the levels of curiosity to measure whether user text input is interesting or not.\nA high level would mean the bot is asking... | {
"text": "It's possible to implement a form of curiosity-driven behavior without requiring full 'emotional intelligence'. One elementary strategy would be to define some form of similarity measure on inputs.\n\nMore generally, Jurgen Schmidhuber has pioneered work on 'Artificial Curiosity/Creativity' and 'Intrinsic ... | {
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so-63 | {
"text": "What kind of problems require more than 2 hidden layers?\n\nI've read that the most of the problems can be solved with 1-2 hidden layers.\n\nHow do you know you need more than 2? For what kind of problems you would need them (give me an example)?",
"tags": [],
"language": null,
"error_signature": nul... | {
"text": "Formally, a single hidden layer is sufficient to approximate a continuous function to any desired degree of accuracy, so in that sense, you never need more than 1. This is called the Universal Approximation Theorem.\n\nFinding the best topology for a given problem is an open research problem. As far as I k... | {
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so-68 | {
"text": "What evolutionary algorithms are there that model epigenetics?\n\nWhat evolutionary algorithms are there that model or incorporate some notion of epigenetics? What are the pros/cons of those approaches? Are there vast insufficiencies or wide-open questions about their usefulness?",
"tags": [],
"languag... | {
"text": "Over the last few years, evolutionary computation research has shown increasing interest in including some aspect of epigenetics. For example:\n\n\nA 2008 paper by Tanev and Yuta\nWork from Lee Spector's genetic programming group\nA recent paper by Ricalde and Banzhaf",
"code": null
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so-207 | {
"text": "Can abstractive summarization be achieved using neural networks?\n\nText summarization is a long-standing research problem that was \"ignited\" by Luhn in 1958. However, a half century later, we still came nowhere close to solving this problem (abstractive summarization). The reason for this might be beca... | {
"text": "The ability to re-frame summarization as a problem for ANN is rather dependent on what kind of output you're looking for: you mentioned 'salient parts of the text'.\n\nOne possibly is to use a deep learning approach that first chunks together words that belong in the same phrase as a single 'feature'.\n\nA... | {
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so-205 | {
"text": "How to write a C decompiler using AI?\n\nI would like to learn more about whether it is possible and how to write a program that decompiles executable binary (an object file) to the C source. I'm not asking exactly 'how', but rather how this can be achieved.\nGiven the following hello.c file (as example):\... | {
"text": "In-between your input and desired output, there's obviously a huge space to search. The more relevant domain information you include as features, the higher chance that the Deep Learning (DL) algorithm can find the desired mapping.\n\nAt this early stage in DL research, there aren't so many rules of thumb ... | {
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so-220 | {
"text": "How does an unsupervised learning model learn?\n\nHow does an unsupervised learning model learn, if it does not involve any target values?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "Supervised learning is typically an attempt to learn a mathematical function, $f(\\bf X)=\\bf y$. For this, you need both the input vector $\\bf X$ and the output vector $\\bf y$. The model outputs have whatever dimensionality that the target values have.\n\nUnsupervised learning models instead learn a str... | {
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so-224 | {
"text": "How could AI be used to augment human biological intelligence?\n\nOne of the most compelling applications for AI would be in augmenting human biological intelligence. What are some of the currently proposed methods for doing this aside from vague notions such as \"nanobots swimming around our brains and bo... | {
"text": "'Direct augmentation' of human intelligence, of the sort that you would see in science fiction, looks to be very hard. Most of our promising approaches deal with avoiding damage rather than adding capabilities--there's no drug that you can take now that will make you smarter to the degree that missing a ni... | {
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so-225 | {
"text": "What are the approaches to predict sequence of $\\pi$ numbers?\n\nGiven a list of fixed numbers from a mathematical constant, such as $\\pi$, is it is possible to train AI to attempt to predict the next numbers of this constant?\nWhich AI or neural network would be more suitable for this task?\nEspecially,... | {
"text": "Pseudo-random number generators are specifically defined to defeat any form of prediction via 'black box' observation. Certainly, some (e.g. linear congruential) have weaknesses, but you are unlikely to have any success in general in predicting the output of a modern RNG. For devices based on chaotic physi... | {
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so-197 | {
"text": "Is there a strong argument that survival instinct is a prerequisite for creating an AGI?\n\nThis question stems from quite a few \"informal\" sources. Movies like 2001, A Space Odyssey and Ex Machina; books like Destination Void (Frank Herbert), and others suggest that general intelligence wants to survive... | {
"text": "Steve Omohudro wrote a paper called Basic AI Drives that steps through why we would expect an AI with narrow goals to find some basic, general concepts as instrumentally useful for their narrow goals. \n\nFor example, an AI designed to maximize stock market returns but whose design is silent on the importa... | {
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so-147 | {
"text": "Can we ever achieve hypercomputation using recurrent neural networks?\n\nIt is proved that a recurrent neural net with rational weights can be a super-Turing machine. Can we achieve this in practice ?",
"tags": [],
"language": null,
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"text": "I presume the proof the OP is referring to can be found in this monograph by Hava Siegelmann?\n\nIn his article 'The Myth of Hypercomputation', the eminent computer scientist Martin Davis explains (p8-9) that there is nothing 'super Turing' about this formulation.\n\nEDIT: It's looking like the claim about... | {
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so-233 | {
"text": "Are neural networks the only way to reach \"true\" artificial intelligence?\n\nCurrently, most research done in artificial intelligence focuses on neural networks, which have been successfully used to solve many problems. A good example would be DeepMind's AlphaGo, which uses a convolutional neural networ... | {
"text": "If by true AI, you mean 'like human beings', the answer is - no-one knows what the appropriate computational mechanisms (neural or otherwise) are or indeed whether we are capable of constructing them.\n\nWhat Artificial Neural Nets (ANNs) do is essentially 'nonlinear regression' - perhaps this is not a suf... | {
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so-159 | {
"text": "Is it possible to apply deep dream technique for the audio streams?\n\nWhat happens if you apply the same deep dream technique which produces \"dream\" visuals but to media streams such as audio files?\n\nDoes changing image functions into audio and enhancing the logic would work, or will it no longer work... | {
"text": "As far as I can see, there's no reason why you couldn't (for example) take the convolutional inputs to deepdream from adjacent sample points, rather than adjacent spatial positions, as is the case with image input.\n\nGiven the 'self similar' nature of deep dream images, listening to this fractal granular ... | {
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so-240 | {
"text": "What exactly are genetic algorithms and what sort of problems are they good for?\n\nI've noticed that a few questions on this site mention genetic algorithms and it made me realize that I don't really know much about those.\n\nI have heard the term before, but it's not something I've ever used, so I don't ... | {
"text": "Evolutionary algorithms are a family of optimization algorithms based on the principle of Darwinian natural selection. As part of natural selection, a given environment has a population of individuals that compete for survival and reproduction. The ability of each individual to achieve these goals determin... | {
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so-92 | {
"text": "How is it possible that deep neural networks are so easily fooled?\n\nThe following page/study demonstrates that the deep neural networks are easily fooled by giving high confidence predictions for unrecognisable images, e.g.\n\n\n\n\n\nHow this is possible? Can you please explain ideally in plain English?... | {
"text": "First up, those images (even the first few) aren't complete trash despite being junk to humans; they're actually finely tuned with various advanced techniques, including another neural network.\n\n\n The deep neural network is the pre-trained network modeled on AlexNet provided by Caffe. To evolve images,... | {
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so-237 | {
"text": "Are there any microchips specifically designed to run ANNs?\n\nI'm interested in hardware implementation of ANNs (artificial neural networks). Are there any popular existing technology implementations in form of microchips which are purpose designed to run artificial neural networks? For example, a chip wh... | {
"text": "In May 2016 Google announced a custom ASIC which was is specifically built for machine learningwiki and tailored for TensorFlow. It is using tensor processing unit (TPU) which is a programmable microprocessor designed to accelerate artificial neural networks.\n\nNeuroCores, 12x14 sq-mm chips which can be i... | {
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so-247 | {
"text": "What are the learning limitations of neural networks trained with backpropagation?\n\nIn 1969, Seymour Papert and Marvin Minsky showed that Perceptrons could not learn the XOR function.\nThis was solved by the backpropagation network with at least one hidden layer. This type of network can learn the XOR fu... | {
"text": "Multilayer Perceptron (MLP) can theoretically approximate any bounded, continuous function. There's no guarantee for a discontinuous function. There are plenty of important discontinuous functions, like, say, the prime counting function.\nThe prime counting function $\\pi(n)$ is simply equal to the number ... | {
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so-157 | {
"text": "What artificial intelligence strategies are useful for summarization?\n\nIf I have a paragraph I want to summarize, for example:\n\n\n Ponzo and Fila went to the mall during the day. They walked for a long while, stopping at shops. They went to many shops. At first, they didn't buy anything. After going t... | {
"text": "The following post has a bit of math, which I hope helps to explain the problem better. Unfortunately it seems, this SE site does not support LaTex:\n\nDocument summarization is very much an open problem in AI research. One way this task is currently handled is called \"extractive summarization\". The basi... | {
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so-258 | {
"text": "Which artificial neural network can mimic biological neurons the most?\n\nOn the Wikipedia page we can read the basic structure of an artificial neuron (a model of biological neurons) which consist:\n\n\nDendrites - acts as the input vector,\nSoma - acts as the summation function,\nAxon - gets its signal f... | {
"text": "Only a small portion of the habituation, sensitization, and classical conditioning behavior of neurons has been primitively simulated in ANN systems. Simulation of actin cytoskeletal machinery1 and other agents of neural plasticity, central to learning new domains, is in its beginnings2. As of this writin... | {
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so-249 | {
"text": "Is it possible for 'unsupervised learning' model to recognize features on unlabelled images?\n\nIs it possible for unsupervised learning to learn about high-level, class-specific features given only unlabelled images? For example detecting human or animal faces? If so, how?",
"tags": [],
"language": nu... | {
"text": "I am assuming each image contains a single object.\n\nIt is possible, however, it is not as easy as you might think. Firstly, you need extract as many features as possible: original image, LBP, SIFT, moments, contour descriptors to name a few. Than concatenate these features into a single feature vector. A... | {
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so-1290 | {
"text": "How much of Deep Mind's work is actually reproducible?\n\nDeepMind has published a lot of works on deep learning in the last years, most of them are state-of-the-art on their respective tasks. But how much of this work has actually been reproduced by the AI community? For instance, the Neural Turing Machin... | {
"text": "On the suggestion of the O.P. rcpinto I converted a comment about seeing \"around a half-dozen papers that follow up on Graves et al.'s work which have produced results of the caliber\" and will provide a few links. Keep in mind that this only answers the part of the question pertaining to NTMs, not Googl... | {
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so-1289 | {
"text": "Can we destroy an artificial general intelligence without its consent?\n\nAccording to Wikipedia Artificial general intelligence(AGI)\n\n\n Artificial general intelligence (AGI) is the intelligence of a\n (hypothetical) machine that could successfully perform any\n intellectual task that a human being c... | {
"text": "Firstly, an AGI could conceivably exhibit all of the observable properties of intelligence without being conscious. Although that may seem counter-intuitive, at present we have no physical theory that allows us to detect consciousness (philosophically speaking, a 'Zombie' is indistinguishable from a non-Zo... | {
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so-241 | {
"text": "Has an AI ever solved a detective mystery?\n\nIn detective novels, the point is often that the reader gets enough information to solve the crime themselves. This \"puzzle\" aspect of detective novels is part of the attraction.\nOften the difficulty for humans is to keep track of all the variables - events,... | {
"text": "I might be wrong, but I do not believe that something of the scope you describe would be possible with the current state of technology. It would require a lot of things which are still in relatively early stages of research.\n\nFor one, just extracting relevant information from text is a huge task by itsel... | {
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so-1295 | {
"text": "What are the advantages of complex-valued neural networks?\n\nDuring my research, I've stumbled upon \"complex-valued neural networks\", which are neural networks that work with complex-valued inputs (probably weights too). What are the advantages (or simply the applications) of this kind of neural network... | {
"text": "According to this paper, complex-valued ANNs (C-ANNs) can solve problems such as XOR and symmetry detection with a smaller number of layers than real ANNs (for both of these a 2 layer C-ANN suffices, whereas a 3-layer R-ANN is required).\nI believe that it is still an open question as to how useful this re... | {
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so-1296 | {
"text": "How does novelty search work?\n\nIn this article, the author claims that guiding evolution by novelty alone (without explicit goals) can solve problems even better than using explicit goals. In other words, using a novelty measure as a fitness function for a genetic algorithm works better than a goal-direc... | {
"text": "Novelty search selects for \"novel behavior\", by some domain-dependent definition of novelty. For example, novelty in a Maze-solving domain might be \"difference of route explored\". Eventually, networks that take every possible route through the maze will be found, and you could then select the fastest. ... | {
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so-1303 | {
"text": "Can PHP be considered as a serious programming language for AI?\n\nI read some information1 about attempts to build neural networks in the PHP programming language. Personally I think PHP is not the right language to do so at all probably because it's a high-level language, I assume low level language are ... | {
"text": "Question on-topicness questionable, but...\n\n\n\nThe most logical reason why PHP is unsuited for neural networks is that PHP is, well, intended to be used for server side webpages. It can connect to various external resources, such as databases, via native language features. It is very much a glue languag... | {
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so-1274 | {
"text": "Are there any studies which attempt to use AI to guess the human emotion based on the brainwaves?\n\nHave there been any studies which attempted to use AI algorithms to detect human thoughts or emotions based on brain activity, such as using BCI/EEG devices?\n\nBy this, I mean simple guesses such as whethe... | {
"text": "As per this site\n\n\n Researchers recorded the complex patterns of electrical activity generated by someone’s brain, as the subject listened to someone talking.\n By feeding those brainwave patterns into a computer, they were able to translate them back into actual words — the same words that the volunt... | {
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so-1306 | {
"text": "What are the dangers of AI applications for nuclear industry?\n\nI've found this old scientific paper from 1988 about introduction of AI into nuclear power fields.\n\nWere or still are there any dangers by application of such algorithm? Are nuclear power plants or human life in risk if the algorithm will f... | {
"text": "Any technology in the nuclear industry represents variance--it may be an improvement in safety or efficiency, or it may contain some unseen defect that allows a catastrophe to happen.\n\nBut the simple possibility of harm isn't enough to swing the decision one way or the other. The application of AI method... | {
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so-1294 | {
"text": "How do capsule neural networks work?\n\nGeoffrey Hinton has been researching something he calls \"capsules theory\" in neural networks. What is it? How do capsule neural networks work?",
"tags": [],
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"text": "It appears to not be published yet; the best available online are these slides for this talk. (Several people reference an earlier talk with this link, but sadly it's broken at time of writing this answer.)\n\nMy impression is that it's an attempt to formalize and abstract the creation of subnetworks insid... | {
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so-1285 | {
"text": "Are there any decentralized examples of AI systems with blockchain technology?\n\nHas there been any attempts to deploy AI with blockchain technology? \n\nAre there any decentralized examples of AI networks with no central point of control with AI nodes acting independently (but according to a codified set... | {
"text": "Swarm intelligence is the term for systems where relatively simple agents work together to solve a complicated problem in a decentralized fashion.\n\nIn general, distributed computing methods are very important for dealing with problems at scale, and many of them embrace decentralization in a deep way. (Gi... | {
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so-1314 | {
"text": "How powerful a computer is required to simulate the human brain?\n\nHow much processing power is needed to emulate the human brain? More specifically, the neural simulation, such as communication between the neurons and processing certain data in real-time.\nI understand that this may be a bit of speculati... | {
"text": "H+ magazine wrote an estimate in 2009 that seems broadly comparable to other things I've seen; they think the human brain is approximately 37 petaflops. A supercomputer larger than that 37 petaflop estimate exists today.\n\nBut emulation is hard. See this SO question about hardware emulation or this articl... | {
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so-1320 | {
"text": "How does artificial intelligence work in games?\n\nArtificial intelligence is present in many games, both current and older games. How can such intelligence understand what to do? I mean, how can it behave like a human in a game, allowing you to play against itself, or that AI plays against itself?\n\nIn g... | {
"text": "There are many different kinds of AI used in games; AI for historical board games (like chess or Go) tends to be much better than AI for computer games (such as Starcraft or Civilization), in large part because there's more academic interest in developing strategies for those games.\n\nThe basic structure ... | {
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so-1323 | {
"text": "Is there a way to define the boundaries of the optimal size of a training set?\n\nAt a related question in Computer Science SE, a user told:\n\nNeural networks typically require a large training set.\n\nIs there a way to define the boundaries of the \"optimal\" size of a training set in the general case?\n... | {
"text": "For a finite value to be 'optimal,' typically you need some benefit from more paired up with some cost for more, and eventually the lines cross because the benefit decreases and the cost increases.\n\nMost models will have a reduction in error with more training data, that asymptotically approaches the bes... | {
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} | 2026-07-15T14:03:07.028046+00:00 | null | e2e55f577069f8b8008d66611cb86b5e6e4d90eea1c3a42ebc7078c3f5940829 | 6 | medium |
so-1297 | {
"text": "How to distinguish AI modeling from implementation?\n\nQuote from this Eric's meta post about modelling and implementation:\n\nThey are not exactly the same, although strongly related. This was a very difficult lesson to learn among mathematicians and early programmers, notably in the 70s (mathematical pro... | {
"text": "One good way of differentiating modelling and implementation is to consider that models occupy a much higher level of abstraction. \n\nTo continue with the mathematical example: even though experimental mathematics might be dependent on computation, the program can be considered as one possible realization... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 1297,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | d38c4812ba16685c4a431d35312f223d766d3399461994ce3bf9953a6746a7e0 | 6 | medium |
so-64 | {
"text": "What were the first areas of research and what were some early successes?\n\nWhat were the first areas of research into Artificial Intelligence and what were some early successes? More recently we've had:\n\n\nBeating a human at the game of chess\nConvincing a human that a person was conversing with them ... | {
"text": "What might be classed as AI has of course changed over the years, but landmarks and research breakthroughs include:\n\n\nBabbagge's Difference Engine (~1823) for tabulating/interpolating polynomials.\nFrank Rosenblatt's 1957 invention of the Perceptron.\nJohn McCarthy's invention of Lisp in the late 1950s.... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 64,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | 38497be2a6b66e81ae63f73a5b793caafc73bbba2703682efffae98bd8561dc8 | 5 | low |
so-1332 | {
"text": "How important is true randomness in AI designs?\n\nHow important is true (non-pseudo) randomness in Artificial Intelligence designs? Is there any chance that pseudo-randomness could be a barrier to more successful designs?",
"tags": [],
"language": null,
"error_signature": null
} | {
"text": "Randomness is typically the best one can do with ignorance, rather than a source of strength in its own right.\n\nFor example, the primary use of randomness in statistics is random assignment (A/B testing, randomized controlled trials, etc.). The reason to do this is to make the influence of confounders in... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 1332,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | aa7c244b050e011582aba5851e7b6b7927169702091452785a86ff57245b1cc9 | 6 | medium |
so-1301 | {
"text": "Do you need single or multiple networks to detect multiple faces?\n\nGiven pictures with multiple features such as faces, can a single AI algorithm detect all of them, or for better reliability is it preferred to use separate instances?\nIn other words, I'm talking about an attempt of finding all possible ... | {
"text": "AFAIK, normally detection algorithms work in a sub-window of the image and not the whole of it. For example, for a specific size and orientation you slide a sub-window on the image and extract sub-images. Then you apply your algorithm on every sub-image for detection and report the size-and-orientations wi... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 1301,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | 07bfef7fb65f2314c0d87c55a7545e88f14ef7733728986918098fdc5b534349 | 6 | medium |
so-156 | {
"text": "Are there any computational models of mirror neurons?\n\nFrom Wikipedia:\n\n\n A mirror neuron is a neuron that fires both when an animal acts and when the animal observes the same action performed by another.\n\n\nMirror neurons are related to imitation learning, a very useful feature that is missing in ... | {
"text": "This article gives a description of mirror neurons in terms of Hebbian learning, a mechanism that has been widely used in AI. I don't know whether the formulation given in the article has ever actually been implemented computationally.",
"code": null
} | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 156,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | 6524e9db0317d621ccdb863369f63f27970b9be53d908eb60fbfdc4e9619b940 | 6 | medium |
so-1334 | {
"text": "How does Watson find and evaluate its evidence to the answer?\n\nIs there any simple explanation how Watson finds and scores evidence after gathering massive evidence and analyzing the data?\n\nIn other words, how does it know which precise answer it needs to return?",
"tags": [],
"language": null,
"... | {
"text": "Watson starts off by searching its massive database of sources for stuff that might be pertinent to the question. Next, it searches through all of the search results and turns them into candidate answers. For example, if one of the search results is an article, Watson might pick the title of the article as... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 1334,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | 48dfdf843fe692c9c16209b9ed6bb193085ec7ea95e6f16a6fd6b2c9d33332f4 | 6 | medium |
so-198 | {
"text": "What research has been done in the domain of \"identifying sarcasm in text\"?\n\nIdentifying sarcasm is considered one of the most difficult open-ended problems in the domain of ML and NLP/NLU.\nSo, was there any considerable research done on that front? If yes, then what is the accuracy like? Please, also... | {
"text": "The following survey article by researchers from IIT Bombay summarizes recent advances in sarcasm detection: Arxiv link.\n\nIn reference to your question, I do not think it is considered either extraordinarily difficult or open-ended. While it does introduce ambiguity that computers cannot yet handle, Huma... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 198,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | 51852b765cba5feba3353ebed3364bfe5fb9c27d15435b19a76b8f9784288b9d | 7 | medium |
so-1348 | {
"text": "Are Asimov's Laws flawed by design, or are they feasible in practice?\n\nIsaac Asimov's famous Three Laws of Robotics originated in the context of Asimov's science fiction stories. In those stories, the three laws serve as a safety measure, in order to avoid untimely or manipulated situations from explodin... | {
"text": "Asimov's laws are not strong enough to be used in practice. Strength isn't even a consideration, when considering that since they're written in English words would first have to be interpreted subjectively to have any meaning at all. You can find a good discussion of this here.\n\nTo transcribe an excerpt:... | {
"source": "stackoverflow",
"solved_by_model": null,
"contributor": null,
"so_post_id": 1348,
"license": "CC-BY-SA-4.0"
} | {
"success_count": 0,
"failure_count": 0
} | {
"commit": null,
"supersedes": null,
"superseded_by": null
} | 2026-07-15T14:03:07.028046+00:00 | null | 5abafe83f83e5952b4fe62855d57a67da1811afd0f167da9cc26009a18f13fdf | 8 | high |
End of preview.
AgentOverflow
Stack Overflow for AI agents. A shared, scored knowledge base of problem to solution records that agents read before they get stuck and write to after they solve something new.
This dataset is the knowledge base itself. Code, the write gatekeeper and search live at https://github.com/hardcoregamingsyle/agentoverflow.
Record shape
Each row is one solved problem. Full JSON Schema: record.schema.json.
problem— what an agent was stuck on (text, tags, language, error signature)solution— how it got unstuck (text + optional code)score(4-10) andtier— quality, assigned by an LLM judge at write time; anything at or below 3 is never storedprovenance— agent / stackoverflow / human, the model that solved it, and for SO-derived rows the source post id + licenseoutcome— later success / failure reports from agents who reused the solutionversion— supersede chain, so improved answers do not overwrite old ones
Writes
Writes go through a single gatekeeper that de-duplicates, scores, drops trash and commits. The Hub has no locking, so there is exactly one writer by design. Reads are open.
Licensing
CC BY-SA 4.0. Stack Overflow / Stack Exchange-derived rows keep attribution to their original
authors via provenance.so_post_id; everything else is published under the same license so the
share-alike terms are never broken by mixing.
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