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data/retrieval_individual-f62bcad9-19c4-430b-a7ba-aa2bfeba99dc.jsonl

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 {"tstamp": 1722416531.2239, "task_type": "retrieval", "type": "chat", "model": "voyage-multilingual-2", "gen_params": {}, "start": 1722416528.7267, "finish": 1722416531.2239, "ip": "", "conv_id": "1c15407f838e46d7bf23b9bf7fc3549f", "model_name": "voyage-multilingual-2", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe test was introduced by Turing in his 1950 paper \"Computing Machinery and Intelligence\" while working at the University of Manchester. It opens with the words: \"I propose to consider the question, 'Can machines think? Because \"thinking\" is difficult to define, Turing chooses to \"replace the question by another, which is closely related to it and is expressed in relatively unambiguous words.\" Turing describes the new form of the problem in terms of a three-person game called the \"imitation game\", in which an interrogator asks questions of a man and a woman in another room in order to determine the correct sex of the two players. Turing's new question is: \"Are there imaginable digital computers which would do well in the imitation game?\" This question, Turing believed, was one that could actually be answered. In the remainder of the paper, he argued against all the major objections to the proposition that \"machines can think\".\nSince Turing introduced his test, it has been both highly influential and widely criticized, and has become an important concept in the philosophy of artificial intelligence. Philosopher John Searle would comment on the Turing test in his Chinese room argument, a thought experiment that stipulates that a machine cannot have a \"mind\", \"understanding\", or \"consciousness\", regardless of how intelligently or human-like the program may make the computer behave. Searle criticizes Turing's test and claims it is insufficient to detect the presence of consciousness.\nHistory"]], "corpus": "wikipedia"}
 {"tstamp": 1722417056.9399, "task_type": "retrieval", "type": "chat", "model": "jinaai/jina-embeddings-v2-base-en", "gen_params": {}, "start": 1722417054.7262, "finish": 1722417056.9399, "ip": "", "conv_id": "7c378110a16a46939419ddf699bc69db", "model_name": "jinaai/jina-embeddings-v2-base-en", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Cognitive test\n\nCognitive tests are assessments of the cognitive capabilities of humans and other animals. Tests administered to humans include various forms of IQ tests; those administered to animals include the mirror test (a test of visual self-awareness) and the T maze test (which tests learning ability). Such testing is used in psychology and psychometrics, as well as other fields studying human and animal intelligence."]], "corpus": "wikipedia"}
 {"tstamp": 1722417056.9399, "task_type": "retrieval", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1722417054.7262, "finish": 1722417056.9399, "ip": "", "conv_id": "981a97a561a44c3589e95b8fa989249b", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct answers to questions, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic)."]], "corpus": "wikipedia"}
+{"tstamp": 1722417895.2027, "task_type": "retrieval", "type": "chat", "model": "voyage-multilingual-2", "gen_params": {}, "start": 1722417892.8706, "finish": 1722417895.2027, "ip": "", "conv_id": "def8ce8866b84f9eb7a5acd864f94c57", "model_name": "voyage-multilingual-2", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe test was introduced by Turing in his 1950 paper \"Computing Machinery and Intelligence\" while working at the University of Manchester. It opens with the words: \"I propose to consider the question, 'Can machines think? Because \"thinking\" is difficult to define, Turing chooses to \"replace the question by another, which is closely related to it and is expressed in relatively unambiguous words.\" Turing describes the new form of the problem in terms of a three-person game called the \"imitation game\", in which an interrogator asks questions of a man and a woman in another room in order to determine the correct sex of the two players. Turing's new question is: \"Are there imaginable digital computers which would do well in the imitation game?\" This question, Turing believed, was one that could actually be answered. In the remainder of the paper, he argued against all the major objections to the proposition that \"machines can think\".\nSince Turing introduced his test, it has been both highly influential and widely criticized, and has become an important concept in the philosophy of artificial intelligence. Philosopher John Searle would comment on the Turing test in his Chinese room argument, a thought experiment that stipulates that a machine cannot have a \"mind\", \"understanding\", or \"consciousness\", regardless of how intelligently or human-like the program may make the computer behave. Searle criticizes Turing's test and claims it is insufficient to detect the presence of consciousness.\nHistory"]], "corpus": "wikipedia"}
+{"tstamp": 1722417895.2027, "task_type": "retrieval", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1722417892.8706, "finish": 1722417895.2027, "ip": "", "conv_id": "55e644149470428d8bfb6fef44781908", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct answers to questions, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic)."]], "corpus": "wikipedia"}
+{"tstamp": 1722417926.6663, "task_type": "retrieval", "type": "chat", "model": "jinaai/jina-embeddings-v2-base-en", "gen_params": {}, "start": 1722417926.4291, "finish": 1722417926.6663, "ip": "", "conv_id": "e0cc71849c35440f9d234f9e39526e46", "model_name": "jinaai/jina-embeddings-v2-base-en", "prompt": "Why did the machines in The Matrix keep humans around?", "output": [["Why did the machines in The Matrix keep humans around?", "Stackoverflow Stackexchange\n\nQ: Can't install gatsby-plugin-sharp.(libpng-dev may not installed) OS: Win 10\nwindows-build-tools is installed.\nWhen I was trying to install gatsby-plugin-sharp with npm install --save gatsby-plugin-sharp. I received two errors.\nI've tried this npm install --save-dev pngquant --msvs_version=2013  as someone mentioned. But it caused the same error with no 'libpng-dev'.\n\\> [email protected] postinstall C:\\Users\\54391\\Documents\\code\\personal-blog\\node_modules\\mozjpeg\n\\> node lib/install.js\n\n‼ getaddrinfo ENOENT raw.githubusercontent.com\n‼ mozjpeg pre-build test failed\ni compiling from source\n× Error: Command failed: C:\\Windows\\system32\\cmd.exe /s /c \"autoreconf -fiv\"\n'autoreconf' �����ڲ����ⲿ���Ҳ���ǿ����еij���\n���������ļ���\n\nat C:\\Users\\54391\\Documents\\code\\personal-blog\\node_modules\\bin-build\\node_modules\\execa\\index.js:231:11\nat runMicrotasks (<anonymous>)\nat processTicksAndRejections (internal/process/task_queues.js:97:5)\nat async Promise.all (index 0)\n\n\\> [email protected] postinstall C:\\Users\\54391\\Documents\\code\\personal-blog\\node_modules\\pngquant-bin\n\\> node lib/install.js\n\n‼ getaddrinfo ENOENT raw.githubusercontent.com\n‼ pngquant pre-build test failed\ni compiling from source\n× Error: pngquant failed to build, make sure that libpng-dev is installed\nat C:\\Users\\54391\\Documents\\code\\personal-blog\\node_modules\\bin-build\\node_modules\\execa\\index.js:231:11\nat processTicksAndRejections (internal/process/task_queues.js:97:5)\nat async Promise.all (index 0)\n\n"]], "corpus": "stackexchange"}
+{"tstamp": 1722417926.6663, "task_type": "retrieval", "type": "chat", "model": "BM25", "gen_params": {}, "start": 1722417926.4291, "finish": 1722417926.6663, "ip": "", "conv_id": "e5c658b4230e481e8478fe37a5adec44", "model_name": "BM25", "prompt": "Why did the machines in The Matrix keep humans around?", "output": [["Why did the machines in The Matrix keep humans around?", "Scifi Stackexchange\n\nQ: What happens to a person after they die in the Matrix? Machines keep humans in the Matrix as they are a source of energy. Why did they make it so that when a human is hurt in the Matrix, they're bodies hurt themselves in real life (in the tank)? If a human dies in the Matrix, do they die in the real world? Or just get flushed out of their tank? Isn't it kind of a waste?\n\nA: The body cannot live without the mind. The machines can't get around that. But nothing is wasted. They liquefy the dead so that they can be fed intravenously to the living.\n\n\n\nJump to 45 seconds for Morpheus' first hand explanation.\n"]], "corpus": "stackexchange"}
+{"tstamp": 1722417993.6565, "task_type": "retrieval", "type": "chat", "model": "jinaai/jina-embeddings-v2-base-en", "gen_params": {}, "start": 1722417991.5371, "finish": 1722417993.6565, "ip": "", "conv_id": "21475786067d41e9b5f96a6adacc3884", "model_name": "jinaai/jina-embeddings-v2-base-en", "prompt": "Please find me the paper on training code large language models to follow instructions via git commits.", "output": [["Please find me the paper on training code large language models to follow instructions via git commits.", "Title: Preferential Partner Selection in an Evolutionary Study of Prisoner's Dilemma\n\nAbstract: Partner selection is an important process in many social interactions, permitting individuals to decrease the risks associated with cooperation. In large populations, defectors may escape punishment by roving from partner to partner, but defectors in smaller populations risk social isolation. We investigate these possibilities for an evolutionary prisoner's dilemma in which agents use expected payoffs to choose and refuse partners. In comparison to random or round-robin partner matching, we find that the average payoffs attained with preferential partner selection tend to be more narrowly confined to a few isolated payoff regions. Most ecologies evolve to essentially full cooperative behavior, but when agents are intolerant of defections, or when the costs of refusal and social isolation are small, we also see the emergence of wallflower ecologies in which all agents are socially isolated. In between these two extremes, we see the emergence of ecologies whose agents tend to engage in a small number of defections followed by cooperation thereafter. The latter ecologies exhibit a plethora of interesting social interaction patterns. Keywords: Evolutionary Game; Iterated Prisoner's Dilemma; Partner Choice and Refusal; Artificial Life; Genetic Algorithm; Finite Automata."]], "corpus": "arxiv"}
+{"tstamp": 1722417993.6565, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722417991.5371, "finish": 1722417993.6565, "ip": "", "conv_id": "d5e0dd0904da4d0d88271ff63387464f", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "Please find me the paper on training code large language models to follow instructions via git commits.", "output": [["Please find me the paper on training code large language models to follow instructions via git commits.", "Title: CommitBERT: Commit Message Generation Using Pre-Trained Programming Language Model\n\nAbstract: Commit message is a document that summarizes source code changes in natural language. A good commit message clearly shows the source code changes, so this enhances collaboration between developers. Therefore, our work is to develop a model that automatically writes the commit message. To this end, we release 345K datasets consisting of code modification and commit messages in six programming languages (Python, PHP, Go, Java, JavaScript, and Ruby). Similar to the neural machine translation (NMT) model, using our dataset, we feed the code modification to the encoder input and the commit message to the decoder input and measure the result of the generated commit message with BLEU-4. Also, we propose the following two training methods to improve the result of generating the commit message: (1) A method of preprocessing the input to feed the code modification to the encoder input. (2) A method that uses an initial weight suitable for the code domain to reduce the gap in contextual representation between programming language (PL) and natural language (NL). Training code, dataset, and pre-trained weights are available at https://github.com/graykode/commit-autosuggestions"]], "corpus": "arxiv"}
+{"tstamp": 1722417994.5447, "task_type": "retrieval", "type": "chat", "model": "jinaai/jina-embeddings-v2-base-en", "gen_params": {}, "start": 1722417992.3387, "finish": 1722417994.5447, "ip": "", "conv_id": "353fa7bb68a94bc4ab7d2d587d4dd488", "model_name": "jinaai/jina-embeddings-v2-base-en", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Cognitive test\n\nCognitive tests are assessments of the cognitive capabilities of humans and other animals. Tests administered to humans include various forms of IQ tests; those administered to animals include the mirror test (a test of visual self-awareness) and the T maze test (which tests learning ability). Such testing is used in psychology and psychometrics, as well as other fields studying human and animal intelligence."]], "corpus": "wikipedia"}
+{"tstamp": 1722417994.5447, "task_type": "retrieval", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1722417992.3387, "finish": 1722417994.5447, "ip": "", "conv_id": "f3bcc1930bfe4f1489adccdc43648247", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe test was introduced by Turing in his 1950 paper \"Computing Machinery and Intelligence\" while working at the University of Manchester. It opens with the words: \"I propose to consider the question, 'Can machines think? Because \"thinking\" is difficult to define, Turing chooses to \"replace the question by another, which is closely related to it and is expressed in relatively unambiguous words.\" Turing describes the new form of the problem in terms of a three-person game called the \"imitation game\", in which an interrogator asks questions of a man and a woman in another room in order to determine the correct sex of the two players. Turing's new question is: \"Are there imaginable digital computers which would do well in the imitation game?\" This question, Turing believed, was one that could actually be answered. In the remainder of the paper, he argued against all the major objections to the proposition that \"machines can think\".\nSince Turing introduced his test, it has been both highly influential and widely criticized, and has become an important concept in the philosophy of artificial intelligence. Philosopher John Searle would comment on the Turing test in his Chinese room argument, a thought experiment that stipulates that a machine cannot have a \"mind\", \"understanding\", or \"consciousness\", regardless of how intelligently or human-like the program may make the computer behave. Searle criticizes Turing's test and claims it is insufficient to detect the presence of consciousness.\nHistory"]], "corpus": "wikipedia"}
+{"tstamp": 1722418019.3162, "task_type": "retrieval", "type": "chat", "model": "jinaai/jina-embeddings-v2-base-en", "gen_params": {}, "start": 1722418019.1398, "finish": 1722418019.3162, "ip": "", "conv_id": "16e0d02092a74e6e9b9e2324ec643d8d", "model_name": "jinaai/jina-embeddings-v2-base-en", "prompt": "Find me a planet near α 23h 06m 29.368s and δ −05° 02′ 29.04″ that could be habitable.", "output": [["Find me a planet near α 23h 06m 29.368s and δ −05° 02′ 29.04″ that could be habitable.", "Planetary habitability\n\nPlanetary habitability is the measure of a planet's or a natural satellite's potential to develop and maintain environments hospitable to life. Life may be generated directly on a planet or satellite endogenously or be transferred to it from another body, through a hypothetical process known as panspermia. Environments do not need to contain life to be considered habitable nor are accepted habitable zones (HZ) the only areas in which life might arise."]], "corpus": "wikipedia"}
+{"tstamp": 1722418019.3162, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722418019.1398, "finish": 1722418019.3162, "ip": "", "conv_id": "04128e2f519a462fad781cf2ce9f75a4", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "Find me a planet near α 23h 06m 29.368s and δ −05° 02′ 29.04″ that could be habitable.", "output": [["Find me a planet near α 23h 06m 29.368s and δ −05° 02′ 29.04″ that could be habitable.", "Habitable zone\n\nK2-18b is an exoplanet 124 light-years away, orbiting in the habitable zone of the K2-18, a red dwarf. This planet is significant for water vapor found in its atmosphere; this was announced on September 17, 2019.\nIn September 2020, astronomers identified 24 superhabitable planet (planets better than Earth) contenders, from among more than 4000 confirmed exoplanets at present, based on astrophysical parameters, as well as the natural history of known life forms on the Earth.\nHabitability outside the HZ\nLiquid-water environments have been found to exist in the absence of atmospheric pressure and at temperatures outside the HZ temperature range. For example, Saturn's moons Titan and Enceladus and Jupiter's moons Europa and Ganymede, all of which are outside the habitable zone, may hold large volumes of liquid water in subsurface oceans.\nOutside the HZ, tidal heating and radioactive decay are two possible heat sources that could contribute to the existence of liquid water. Abbot and Switzer (2011) put forward the possibility that subsurface water could exist on rogue planets as a result of radioactive decay-based heating and insulation by a thick surface layer of ice.\nWith some theorising that life on Earth may have actually originated in stable, subsurface habitats, it has been suggested that it may be common for wet subsurface extraterrestrial habitats such as these to 'teem with life'. On Earth itself, living organisms may be found more than  below the surface."]], "corpus": "wikipedia"}