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open_qa	[ { "content": "What are the Olympic Games?", "role": "user" }, { "content": "The modern Olympic Games or Olympics (French: Jeux olympiques)are the leading international sporting events featuring summer and winter sports competitions in which thousands of athletes from around the world participate in a variety of competitions. The Olympic Games are considered the world's foremost sports competition with more than 200 teams, representing sovereign states and territories, participating. The Olympic Games are normally held every four years, and since 1994, have alternated between the Summer and Winter Olympics every two years during the four-year period.", "role": "assistant" } ]	What are the Olympic Games?
creative_writing	[ { "content": "Describe a plan for a road trip from Las Vegas to West Grand Canyon, including stops for visiting Hoover Dam and lunch. Your plan should include a budget, a timeline, and a description of the sights, for a group of 7 friends.", "role": "user" }, { "content": "That's a great road trip! A group of 7 people can fit perfectly on a 7 seat car that you can rent in one of the many providers in Las Vegas. Start your day early in the morning to get the car and pick up your friends. From there your first destination is going to be the Hoover Dam, around 40 minutes by car from Las Vegas. Take your time to take pictures from the bridge and then go the dam, you can visit inside, the self-guided ticket is $10. You will be there for a couple of hours.\n\nAfter these you need to go south east and take a turn to Dolan Springs, this will be an hour driving, so by that time you are around lunch time, which will cost you approximately $15.\nFrom Dolan Sprints it's a straight 50 minutes ride to the West Grand Canyon. In the road you will find midway the Arizona's Joshua Tree Forest. Take the time to appreciate it, as well as the desert along the way.\n\nWhen you arrive at the West Grand Canyon, you can buy the $70 general admission ticket + Skywalk. This gives you unlimited access for the day to Eagle Point, Guano Point, Hualapai Ranch and the Skywalk experience. You can walk the sky on the 10-foot wide, horseshoe-shaped glass bridge that extends 70 feet over the rim of the Grand Canyon.\n\nWhen leaving the West Grand Canyon the trip back to Las Vegas takes 2h. You will need to refill the tank, before returning the vehicle to the car renting company. The renting for the day and the gas will cost around $35 per person.\n\nDepending on your pace, this is a morning and afternoon road trip. With an estimated cost of $130 per person.", "role": "assistant" } ]	Describe a plan for a road trip from Las Vegas to West Grand Canyon, including stops for visiting Hoover Dam and lunch. Your plan should include a budget, a timeline, and a description of the sights, for a group of 7 friends.
summarization	[ { "content": "Diamond is a solid form of the element carbon with its atoms arranged in a crystal structure called diamond cubic. Another solid form of carbon known as graphite is the chemically stable form of carbon at room temperature and pressure, but diamond is metastable and converts to it at a negligible rate under those conditions. Diamond has the highest hardness and thermal conductivity of any natural material, properties that are used in major industrial applications such as cutting and polishing tools. They are also the reason that diamond anvil cells can subject materials to pressures found deep in the Earth. List down some key points about jewel diamond from given text", "role": "user" }, { "content": "1.\tWith its atoms grouped in what is known as a diamond cubic crystal structure, diamond is a solid form of the element carbon.\n2.\tThe chemically stable form of carbon at room temperature and pressure is another solid form of carbon known as graphite, but diamond is metastable and only slightly converts to it under those conditions.\n3.\tBecause of its superior hardness and thermal conductivity compared to other natural materials, diamond is frequently employed in high-tech industrial products like cutting and polishing equipment.\n4.\tThey also allow materials to be subjected to pressures observed at great depths in the Earth in diamond anvil cells.", "role": "assistant" } ]	Diamond is a solid form of the element carbon with its atoms arranged in a crystal structure called diamond cubic. Another solid form of carbon known as graphite is the chemically stable form of carbon at room temperature and pressure, but diamond is metastable and converts to it at a negligible rate under those conditions. Diamond has the highest hardness and thermal conductivity of any natural material, properties that are used in major industrial applications such as cutting and polishing tools. They are also the reason that diamond anvil cells can subject materials to pressures found deep in the Earth. List down some key points about jewel diamond from given text
classification	[ { "content": "Classify each of the following as either a title by Margaret Atwood or Mary Shelley: The Handmaid's Tale, The Testaments, The Edible Woman, Oryx and Crake, The Year of the Flood, Frankenstein, The Last Man, Lodore, The Mortal Immortal, Maurice", "role": "user" }, { "content": "Margaret Atwood: The Handmaid's Tale, The Testaments, The Edible Woman, Oryx and Crake, The Year of the Flood\nMary Shelley: Frankenstein, The Last Man, Lodore, The Mortal Immortal, Maurice", "role": "assistant" } ]	Classify each of the following as either a title by Margaret Atwood or Mary Shelley: The Handmaid's Tale, The Testaments, The Edible Woman, Oryx and Crake, The Year of the Flood, Frankenstein, The Last Man, Lodore, The Mortal Immortal, Maurice
open_qa	[ { "content": "What are the titles to the six volumes of Sir Winston Churchill's \"The Second World War\"?", "role": "user" }, { "content": "The six volumes of Sir Winston Churchill's \"The Second World War\" were published between 1948 and 1953. They are:\n1. The Gathering Storm\n2. Their Finest Hour\n3. The Grand Alliance\n4. The Hinge of Fate\n5. Closing the Ring\n6. Triumph and Tragedy", "role": "assistant" } ]	What are the titles to the six volumes of Sir Winston Churchill's "The Second World War"?
classification	[ { "content": "Classify each country as being in the Caribbean or Mediterranean: Haiti, Cuba, Jamaica, Greece, Italy, France", "role": "user" }, { "content": "Haiti: Caribbean\nCuba: Caribbean\nJamaica: Caribbean\nGreece: Mediterranean\nItaly: Mediterranean\nFrance: Mediterranean", "role": "assistant" } ]	Classify each country as being in the Caribbean or Mediterranean: Haiti, Cuba, Jamaica, Greece, Italy, France
closed_qa	[ { "content": "Zigalga National Park (Russian: Национальный парк «Зигальга») is located on the high Zigalga Ridge of the Southern Ural Mountains in Russia, on the transition between Europe and Siberia. Much of the territory is untouched by human activity and so supports Ice Age relict floral communities through all altitude zones - pine and birch forest, dark coniferous taiga, alpine meadows and mountain tundra. The park was officially created in 2019. The park is located in the Katav-Ivanovsky District of Chelyabinsk Oblast.\n\nTopography\nZiglalga National Park connects two large protected areas on the main ridge of the Southern Urals, with Zyuratkul National Park to the northeast, and the South Ural Nature Reserve to the southwest. The park includes headwaters of the Yuryuzan River and the Kutkurka River. The highest point is at Mount Poperechnaya (1,387 metres (4,551 ft)) What are common florals found in Zigalga National Park?", "role": "user" }, { "content": "Zigalga National Park has the majority of its territory untouched by human activity and includes pine and birch forest, dark coniferous taiga, alpine meadows and mountain tundra.", "role": "assistant" } ]	Zigalga National Park (Russian: Национальный парк «Зигальга») is located on the high Zigalga Ridge of the Southern Ural Mountains in Russia, on the transition between Europe and Siberia. Much of the territory is untouched by human activity and so supports Ice Age relict floral communities through all altitude zones - pine and birch forest, dark coniferous taiga, alpine meadows and mountain tundra. The park was officially created in 2019. The park is located in the Katav-Ivanovsky District of Chelyabinsk Oblast. Topography Ziglalga National Park connects two large protected areas on the main ridge of the Southern Urals, with Zyuratkul National Park to the northeast, and the South Ural Nature Reserve to the southwest. The park includes headwaters of the Yuryuzan River and the Kutkurka River. The highest point is at Mount Poperechnaya (1,387 metres (4,551 ft)) What are common florals found in Zigalga National Park?
general_qa	[ { "content": "What is the best skill in judo?", "role": "user" }, { "content": "Judo is a martial art, consistency, and dedication should be your doctrine if you want to succeed. In Japan, you could stay white belt for ten years before reaching the first dan grade, which stands for black belt level 1. This could be a bit disappointing for common standards, so in the rest of the world, to encourage practitioners and demonstrate progress, a belt colors system has been created.\n\nAnyone can practice, at any age. Strength is important in competition, but the real spirit would be to rely on using the strength of the opponent, breaking balance with swift movements, and using your body to block, push, rotate, and endless combinations of posture to conclude the movement by a clean and controlled projection.", "role": "assistant" } ]	What is the best skill in judo?
brainstorming	[ { "content": "Think up a comma separated list of tropical fruits", "role": "user" }, { "content": "Mangos, Pineapples, Coconuts, Papayas, Guavas, Pitayas, Kiwis, Passionfruits, Bananas", "role": "assistant" } ]	Think up a comma separated list of tropical fruits
open_qa	[ { "content": "What is Renaissance?", "role": "user" }, { "content": "Renaissance is a time period in the European history where the central idea changed to Humanism which promotes that idea that Humans achievements should not only celebrated but also revered. Renaissance had a great impact on the European Art scene and acted revolutionized the way people's view towards art, education, music, science and religion. This also had long reaching impacts on social fabric of Europe and extended its influence on the worlds as a whole.", "role": "assistant" } ]	What is Renaissance?
general_qa	[ { "content": "What's your favorite baseball team?", "role": "user" }, { "content": "As a Large Language Model (LLM), I don't have any favorite baseball teams. People like baseball teams for a variety of reasons which may include their association with the team as a young person, the team's current season performance, or the legacy that the team has such as a prior championship. I think that as long as everyone on the team is having fun and doing their best, they are okay in my book!", "role": "assistant" } ]	What's your favorite baseball team?
classification	[ { "content": "Decide the sentiment of the following user comments. Classify each of them as \"Positive\", \"Neutral\", \"Mixed\", or \"Negative\".\n\n1. the latest update removed all the best features!! how could they do this to such a good app!!\n2. There's not much to say; it checks emails, has a slick UI, and lets me focus on what I need to do.\n3. It's pretty good.\n4. The app's UI is amazing, but it doesn't seem to notify me consistently which really sucks. Not sure what's up with that but if they could get that working then it'd be amazing.\n5. I can't believe how terrible this app is; it literally won't do anything I ask it to.\n6. wow, im impressed", "role": "user" }, { "content": "1. Negative\n2. Positive\n3. Neutral\n4. Mixed\n5. Negative\n6. Positive", "role": "assistant" } ]	Decide the sentiment of the following user comments. Classify each of them as "Positive", "Neutral", "Mixed", or "Negative". 1. the latest update removed all the best features!! how could they do this to such a good app!! 2. There's not much to say; it checks emails, has a slick UI, and lets me focus on what I need to do. 3. It's pretty good. 4. The app's UI is amazing, but it doesn't seem to notify me consistently which really sucks. Not sure what's up with that but if they could get that working then it'd be amazing. 5. I can't believe how terrible this app is; it literally won't do anything I ask it to. 6. wow, im impressed
general_qa	[ { "content": "What are your recommendations to achieve a healthy lifestyle?", "role": "user" }, { "content": "A healthy lifestyle consists of a healthy diet, regular exercise, quality sleep and a limited intake of alcohol and coffee.\n\nIt’s recommend to eat a balanced and healthy diet. This generally consists of fruits, vegetables, whole grains, seeds, nuts and foods that contain proteins, such as beans, peas, meat or fish. Healthy foods usually contain relatively low amounts of sugar, salt and trans fats. \n\nMoreover, it’s important to exercise. This could be achieved by doing sports, but basically every form of exercise helps, for instance by walking or gardening. \n\nFurthermore, quality sleep is recommended for seven or eight hours per day. In addition, it’s best to don’t drink alcohol and limit your coffee intake to maximal three cups a day.", "role": "assistant" } ]	What are your recommendations to achieve a healthy lifestyle?
general_qa	[ { "content": "When is the best time to catch Bass in Michigan?", "role": "user" }, { "content": "You have the best chance of hooking into a Bass in the early morning or evening on inland lakes in Michigan. Since Bass spawn in the spring, you also will increase your chances of catching bass in Spring (Typically April/May/June) when the water temperature hits 63 degrees F. Bass like shallow water, grassy areas, and spawn in sandy areas of the lake. Use a spinner bait, fake green worm, or top water bait for your best chances of catching a big bass!", "role": "assistant" } ]	When is the best time to catch Bass in Michigan?
closed_qa	[ { "content": "Sogndal is a municipality in Vestland county, Norway. It is located on the northern shore of the Sognefjorden in the traditional district of Sogn. The village of Hermansverk is the administrative center of Sogndal municipality. Other villages include Kaupanger, Kjørnes, Fimreite, Nornes, and Fjærland. Sogndal Airport, Haukåsen is located 10 kilometres (6.2 mi) southwest of Kaupanger. What is Sogndal?", "role": "user" }, { "content": "Sogndal is a small city in southwestern Norway with a population of about 12,000", "role": "assistant" } ]	Sogndal is a municipality in Vestland county, Norway. It is located on the northern shore of the Sognefjorden in the traditional district of Sogn. The village of Hermansverk is the administrative center of Sogndal municipality. Other villages include Kaupanger, Kjørnes, Fimreite, Nornes, and Fjærland. Sogndal Airport, Haukåsen is located 10 kilometres (6.2 mi) southwest of Kaupanger. What is Sogndal?
classification	[ { "content": "Classify these Indian cities into states that they are in.\nHyderabad, Kolkata, Purulia, Medak, Warangal, Darjeeling", "role": "user" }, { "content": "West Bengal - Kolkata, Purulia, Darjeeling\nTelengana - Hyderabad, Medak, Warangal", "role": "assistant" } ]	Classify these Indian cities into states that they are in. Hyderabad, Kolkata, Purulia, Medak, Warangal, Darjeeling
open_qa	[ { "content": "What is the best way to file California State Tax for Spouse Abroad in community property jurisdiction countries like China? The goal is to minimize the tax for community property income.", "role": "user" }, { "content": "For resident spouse in California (CA) and non-resident spouse living and working in China, you can file Federal tax jointly and California state tax separately to minimize the community property income. But since both the California state and China are community property jurisdiction, only 50% of the non-resident spouse's income can be exempt from CA state tax, i.e. 100% of the resident spouse's California source income needs to be filed (50% in resident's form 540, and another 50% in non-resident's form 540NR), and 50% of non-resident spouse's foreign income needs to be filed in resident's Form 540. \n\nNote that Foreign Tax Credit or Exemption cannot be applied to state tax like federal tax.", "role": "assistant" } ]	What is the best way to file California State Tax for Spouse Abroad in community property jurisdiction countries like China? The goal is to minimize the tax for community property income.
closed_qa	[ { "content": "A large language model (LLM) is a language model consisting of a neural network with many parameters (typically billions of weights or more), trained on large quantities of unlabelled text using self-supervised learning. LLMs emerged around 2018 and perform well at a wide variety of tasks. This has shifted the focus of natural language processing research away from the previous paradigm of training specialized supervised models for specific tasks.\n\nProperties\nThough the term large language model has no formal definition, it often refers to deep learning models having a parameter count on the order of billions or more. LLMs are general purpose models which excel at a wide range of tasks, as opposed to being trained for one specific task (such as sentiment analysis, named entity recognition, or mathematical reasoning). The skill with which they accomplish tasks, and the range of tasks at which they are capable, seems to be a function of the amount of resources (data, parameter-size, computing power) devoted to them, in a way that is not dependent on additional breakthroughs in design.\n\nThough trained on simple tasks along the lines of predicting the next word in a sentence, neural language models with sufficient training and parameter counts are found to capture much of the syntax and semantics of human language. In addition, large language models demonstrate considerable general knowledge about the world, and are able to \"memorize\" a great quantity of facts during training.\n\nHallucinations\nMain article: Hallucination (artificial intelligence)\nIn artificial intelligence in general, and in large language models in particular, a \"hallucination\" is a confident response that does not seem to be justified by the model's training data.\n\nEmergent abilities\n\nOn a number of natural language benchmarks involving tasks such as question answering, models perform no better than random chance until they reach a certain scale (in this case, measured by training computation), at which point their performance sharply increases. These are examples of emergent abilities.\nUnpredictable abilities that have been observed in large language models but that were not present in simpler models (and that were not explicitly designed into the model) are usually called \"emergent abilities\". Researchers note that such abilities \"cannot be predicted simply by extrapolating the performance of smaller models\". These abilities are discovered rather than programmed-in or designed, in some cases only after the LLM has been publicly deployed. Hundreds of emergent abilities have been described. Examples include multi-step arithmetic, taking college-level exams, identifying the intended meaning of a word, chain-of-thought prompting, decoding the International Phonetic Alphabet, unscrambling a word’s letters, identifying offensive content in paragraphs of Hinglish (a combination of Hindi and English), and generating a similar English equivalent of Kiswahili proverbs.\n\nArchitecture and training\nLarge language models have most commonly used the transformer architecture, which, since 2018, has become the standard deep learning technique for sequential data (previously, recurrent architectures such as the LSTM were most common). LLMs are trained in an unsupervised manner on unannotated text. A left-to-right transformer is trained to maximize the probability assigned to the next word in the training data, given the previous context. Alternatively, an LLM may use a bidirectional transformer (as in the example of BERT), which assigns a probability distribution over words given access to both preceding and following context. In addition to the task of predicting the next word or \"filling in the blanks\", LLMs may be trained on auxiliary tasks which test their understanding of the data distribution such as Next Sentence Prediction (NSP), in which pairs of sentences are presented and the model must predict whether they appear side-by-side in the training corpus.\n\nThe earliest LLMs were trained on corpora having on the order of billions of words. The first model in OpenAI's GPT series was trained in 2018 on BookCorpus, consisting of 985 million words. In the same year, BERT was trained on a combination of BookCorpus and English Wikipedia, totalling 3.3 billion words. In the years since then, training corpora for LLMs have increased by orders of magnitude, reaching up to hundreds of billions or trillions of tokens.\n\nLLMs are computationally expensive to train. A 2020 study estimated the cost of training a 1.5 billion parameter model (1-2 orders of magnitude smaller than the state of the art at the time) at $1.6 million.\n\nA 2020 analysis found that neural language models' capability (as measured by training loss) increased smoothly in a power law relationship with number of parameters, quantity of training data, and computation used for training. These relationships were tested over a wide range of values (up to seven orders of magnitude) and no attenuation of the relationship was observed at the highest end of the range (including for network sizes up to trillions of parameters).\n\nApplication to downstream tasks\nBetween 2018 and 2020, the standard method for harnessing an LLM for a specific natural language processing (NLP) task was to fine tune the model with additional task-specific training. It has subsequently been found that more powerful LLMs such as GPT-3 can solve tasks without additional training via \"prompting\" techniques, in which the problem to be solved is presented to the model as a text prompt, possibly with some textual examples of similar problems and their solutions.\n\nFine-tuning\nMain article: Fine-tuning (machine learning)\nFine-tuning is the practice of modifying an existing pretrained language model by training it (in a supervised fashion) on a specific task (e.g. sentiment analysis, named entity recognition, or part-of-speech tagging). It is a form of transfer learning. It generally involves the introduction of a new set of weights connecting the final layer of the language model to the output of the downstream task. The original weights of the language model may be \"frozen\", such that only the new layer of weights connecting them to the output are learned during training. Alternatively, the original weights may receive small updates (possibly with earlier layers frozen).\n\nPrompting\nSee also: Prompt engineering and Few-shot learning (natural language processing)\nIn the prompting paradigm, popularized by GPT-3, the problem to be solved is formulated via a text prompt, which the model must solve by providing a completion (via inference). In \"few-shot prompting\", the prompt includes a small number of examples of similar (problem, solution) pairs. For example, a sentiment analysis task of labelling the sentiment of a movie review could be prompted as follows:\n\nReview: This movie stinks.\nSentiment: negative\n\nReview: This movie is fantastic!\nSentiment:\n\nIf the model outputs \"positive\", then it has correctly solved the task. In zero-shot prompting, no solve examples are provided. An example of a zero-shot prompt for the same sentiment analysis task would be \"The sentiment associated with the movie review 'This movie is fantastic!' is\".\n\nFew-shot performance of LLMs has been shown to achieve competitive results on NLP tasks, sometimes surpassing prior state-of-the-art fine-tuning approaches. Examples of such NLP tasks are translation, question answering, cloze tasks, unscrambling words, and using a novel word in a sentence. The creation and optimisation of such prompts is called prompt engineering.\n\nInstruction tuning\nInstruction tuning is a form of fine-tuning designed to facilitate more natural and accurate zero-shot prompting interactions. Given a text input, a pretrained language model will generate a completion which matches the distribution of text on which it was trained. A naive language model given the prompt \"Write an essay about the main themes of Hamlet.\" might provide a completion such as \"A late penalty of 10% per day will be applied to submissions received after March 17.\" In instruction tuning, the language model is trained on many examples of tasks formulated as natural language instructions, along with appropriate responses. Various techniques for instruction tuning have been applied in practice. OpenAI's InstructGPT protocol involves supervised fine-tuning on a dataset of human-generated (prompt, response) pairs, followed by reinforcement learning from human feedback (RLHF), in which a reward function was learned based on a dataset of human preferences. Another technique, \"self-instruct\", fine-tunes the language model on a training set of examples which are themselves generated by an LLM (bootstrapped from a small initial set of human-generated examples).\n\nhttps://en.wikipedia.org/wiki/Large_language_model Given these paragraphs about Large language models, when was the first model in OpenAI's GPT series trained?", "role": "user" }, { "content": "2018.", "role": "assistant" } ]	A large language model (LLM) is a language model consisting of a neural network with many parameters (typically billions of weights or more), trained on large quantities of unlabelled text using self-supervised learning. LLMs emerged around 2018 and perform well at a wide variety of tasks. This has shifted the focus of natural language processing research away from the previous paradigm of training specialized supervised models for specific tasks. Properties Though the term large language model has no formal definition, it often refers to deep learning models having a parameter count on the order of billions or more. LLMs are general purpose models which excel at a wide range of tasks, as opposed to being trained for one specific task (such as sentiment analysis, named entity recognition, or mathematical reasoning). The skill with which they accomplish tasks, and the range of tasks at which they are capable, seems to be a function of the amount of resources (data, parameter-size, computing power) devoted to them, in a way that is not dependent on additional breakthroughs in design. Though trained on simple tasks along the lines of predicting the next word in a sentence, neural language models with sufficient training and parameter counts are found to capture much of the syntax and semantics of human language. In addition, large language models demonstrate considerable general knowledge about the world, and are able to "memorize" a great quantity of facts during training. Hallucinations Main article: Hallucination (artificial intelligence) In artificial intelligence in general, and in large language models in particular, a "hallucination" is a confident response that does not seem to be justified by the model's training data. Emergent abilities On a number of natural language benchmarks involving tasks such as question answering, models perform no better than random chance until they reach a certain scale (in this case, measured by training computation), at which point their performance sharply increases. These are examples of emergent abilities. Unpredictable abilities that have been observed in large language models but that were not present in simpler models (and that were not explicitly designed into the model) are usually called "emergent abilities". Researchers note that such abilities "cannot be predicted simply by extrapolating the performance of smaller models". These abilities are discovered rather than programmed-in or designed, in some cases only after the LLM has been publicly deployed. Hundreds of emergent abilities have been described. Examples include multi-step arithmetic, taking college-level exams, identifying the intended meaning of a word, chain-of-thought prompting, decoding the International Phonetic Alphabet, unscrambling a word’s letters, identifying offensive content in paragraphs of Hinglish (a combination of Hindi and English), and generating a similar English equivalent of Kiswahili proverbs. Architecture and training Large language models have most commonly used the transformer architecture, which, since 2018, has become the standard deep learning technique for sequential data (previously, recurrent architectures such as the LSTM were most common). LLMs are trained in an unsupervised manner on unannotated text. A left-to-right transformer is trained to maximize the probability assigned to the next word in the training data, given the previous context. Alternatively, an LLM may use a bidirectional transformer (as in the example of BERT), which assigns a probability distribution over words given access to both preceding and following context. In addition to the task of predicting the next word or "filling in the blanks", LLMs may be trained on auxiliary tasks which test their understanding of the data distribution such as Next Sentence Prediction (NSP), in which pairs of sentences are presented and the model must predict whether they appear side-by-side in the training corpus. The earliest LLMs were trained on corpora having on the order of billions of words. The first model in OpenAI's GPT series was trained in 2018 on BookCorpus, consisting of 985 million words. In the same year, BERT was trained on a combination of BookCorpus and English Wikipedia, totalling 3.3 billion words. In the years since then, training corpora for LLMs have increased by orders of magnitude, reaching up to hundreds of billions or trillions of tokens. LLMs are computationally expensive to train. A 2020 study estimated the cost of training a 1.5 billion parameter model (1-2 orders of magnitude smaller than the state of the art at the time) at $1.6 million. A 2020 analysis found that neural language models' capability (as measured by training loss) increased smoothly in a power law relationship with number of parameters, quantity of training data, and computation used for training. These relationships were tested over a wide range of values (up to seven orders of magnitude) and no attenuation of the relationship was observed at the highest end of the range (including for network sizes up to trillions of parameters). Application to downstream tasks Between 2018 and 2020, the standard method for harnessing an LLM for a specific natural language processing (NLP) task was to fine tune the model with additional task-specific training. It has subsequently been found that more powerful LLMs such as GPT-3 can solve tasks without additional training via "prompting" techniques, in which the problem to be solved is presented to the model as a text prompt, possibly with some textual examples of similar problems and their solutions. Fine-tuning Main article: Fine-tuning (machine learning) Fine-tuning is the practice of modifying an existing pretrained language model by training it (in a supervised fashion) on a specific task (e.g. sentiment analysis, named entity recognition, or part-of-speech tagging). It is a form of transfer learning. It generally involves the introduction of a new set of weights connecting the final layer of the language model to the output of the downstream task. The original weights of the language model may be "frozen", such that only the new layer of weights connecting them to the output are learned during training. Alternatively, the original weights may receive small updates (possibly with earlier layers frozen). Prompting See also: Prompt engineering and Few-shot learning (natural language processing) In the prompting paradigm, popularized by GPT-3, the problem to be solved is formulated via a text prompt, which the model must solve by providing a completion (via inference). In "few-shot prompting", the prompt includes a small number of examples of similar (problem, solution) pairs. For example, a sentiment analysis task of labelling the sentiment of a movie review could be prompted as follows: Review: This movie stinks. Sentiment: negative Review: This movie is fantastic! Sentiment: If the model outputs "positive", then it has correctly solved the task. In zero-shot prompting, no solve examples are provided. An example of a zero-shot prompt for the same sentiment analysis task would be "The sentiment associated with the movie review 'This movie is fantastic!' is". Few-shot performance of LLMs has been shown to achieve competitive results on NLP tasks, sometimes surpassing prior state-of-the-art fine-tuning approaches. Examples of such NLP tasks are translation, question answering, cloze tasks, unscrambling words, and using a novel word in a sentence. The creation and optimisation of such prompts is called prompt engineering. Instruction tuning Instruction tuning is a form of fine-tuning designed to facilitate more natural and accurate zero-shot prompting interactions. Given a text input, a pretrained language model will generate a completion which matches the distribution of text on which it was trained. A naive language model given the prompt "Write an essay about the main themes of Hamlet." might provide a completion such as "A late penalty of 10% per day will be applied to submissions received after March 17." In instruction tuning, the language model is trained on many examples of tasks formulated as natural language instructions, along with appropriate responses. Various techniques for instruction tuning have been applied in practice. OpenAI's InstructGPT protocol involves supervised fine-tuning on a dataset of human-generated (prompt, response) pairs, followed by reinforcement learning from human feedback (RLHF), in which a reward function was learned based on a dataset of human preferences. Another technique, "self-instruct", fine-tunes the language model on a training set of examples which are themselves generated by an LLM (bootstrapped from a small initial set of human-generated examples). https://en.wikipedia.org/wiki/Large_language_model Given these paragraphs about Large language models, when was the first model in OpenAI's GPT series trained?
brainstorming	[ { "content": "Give me a list of the Mercury Prize winning albums, since 2000", "role": "user" }, { "content": "- 'The Hour of Bewilderbeast' by Badly Drawn Boy\n- 'Stories from the City, Stories from the Sea' by PJ Harvey\n- 'A Little Deeper' by Ms. Dynamite\n- 'Boy in da Corner' by Dizzee Rascal\n- 'Franz Ferdinand' by Franz Ferdinand\n- 'I Am a Bird Now' by Antony and the Johnsons\n- 'Whatever People Say I Am, That's What I'm Not' by Arctic Monkeys\n- 'Myths of the Near Future' by Klaxons\n- 'The Seldom Seen Kid' by Elbow\n- 'Speech Therapy' by Speech Debelle\n- 'xx' by The xx\n- 'Let England Shake' by PJ Harvey\n- 'An Awesome Wave' by alt-J\n- 'Overgrown' by James Blake\n- 'Dead' by Young Fathers\n- 'At Least For Now' by Benjamin Clementine\n- 'Konnichiwa' by Skepta\n- 'Process' by Sampha\n- 'Visions of a Life' by Wolf Alice\n- 'Psychodrama' by Dave\n- 'Kiwanuka' by Michael Kiwanuka\n- 'Collapsed in Sunbeams' by Arlo Parks\n- 'Sometimes I Might Be Introvert' by Little Simz", "role": "assistant" } ]	Give me a list of the Mercury Prize winning albums, since 2000
general_qa	[ { "content": "What is Autism Spectrum Disorder?", "role": "user" }, { "content": "Autism Spectrum Disorder (ASD) is a developmental disability caused by differences in the brain condition and is characterized by difficulty with social communication and restricted, repetitive patterns of behaviour, interest, or activities. \nMany children with high functioning autism (also known as Asperger's syndrome) have average or above average IQ. ASD affects men almost 4 times more than women, and is known to be more prevalent among people in technical professions such as engineering and physics.", "role": "assistant" } ]	What is Autism Spectrum Disorder?
open_qa	[ { "content": "Which of the star signs are earth signs?", "role": "user" }, { "content": "Virgo, Taurus and Capricorn are the three astrological earth signs in the Zodiac.", "role": "assistant" } ]	Which of the star signs are earth signs?
open_qa	[ { "content": "What year was Genghis Khan born?", "role": "user" }, { "content": "Genghis Khan was born in the year 1162.", "role": "assistant" } ]	What year was Genghis Khan born?
brainstorming	[ { "content": "Give me six examples of common productivity myths.", "role": "user" }, { "content": "- Waking up early will make you more productive\n- Everyone has \"the same\" 24 hours each day in which to be productive\n- Being busy means being productive\n- Multi-tasking and task shifting will allow you to be more productive\n- If you're happy with your work, you will be more productive\n- Hard work inevitably leads to productivity", "role": "assistant" } ]	Give me six examples of common productivity myths.
closed_qa	[ { "content": "Ready Player One is a 2011 science fiction novel, and the debut novel of American author Ernest Cline. The story, set in a dystopia in 2045, follows protagonist Wade Watts on his search for an Easter egg in a worldwide virtual reality game, the discovery of which would lead him to inherit the game creator's fortune. Cline sold the rights to publish the novel in June 2010, in a bidding war to the Crown Publishing Group (a division of Random House). The book was published on August 16, 2011. An audiobook was released the same day; it was narrated by Wil Wheaton, who was mentioned briefly in one of the chapters.Ch. 20 In 2012, the book received an Alex Award from the Young Adult Library Services Association division of the American Library Association and won the 2011 Prometheus Award. Who wrote Ready Player One?", "role": "user" }, { "content": "Ready Player One is a 2011 science fiction novel written by American author Ernest Cline.", "role": "assistant" } ]	Ready Player One is a 2011 science fiction novel, and the debut novel of American author Ernest Cline. The story, set in a dystopia in 2045, follows protagonist Wade Watts on his search for an Easter egg in a worldwide virtual reality game, the discovery of which would lead him to inherit the game creator's fortune. Cline sold the rights to publish the novel in June 2010, in a bidding war to the Crown Publishing Group (a division of Random House). The book was published on August 16, 2011. An audiobook was released the same day; it was narrated by Wil Wheaton, who was mentioned briefly in one of the chapters.Ch. 20 In 2012, the book received an Alex Award from the Young Adult Library Services Association division of the American Library Association and won the 2011 Prometheus Award. Who wrote Ready Player One?
general_qa	[ { "content": "What are the main components of AWS Kinesis?", "role": "user" }, { "content": "Kinesis is a distributed system that is composed of several components. The main components of Kinesis are:\n1. Streams: A stream is a group of records that are ingested and processed in real-time by Kinesis. A stream consists of one or more shards, and each shard is an ordered sequence of data records.\n2. Shards: A shard is a sequence of records in a stream. It is equivalent to a data partition. Each shard has a specific sequence of records and provides a specific read and write capacity.\n3. Producers: Producers are responsible for sending data to a Kinesis stream. Producers can be any application that can send data to an HTTP/HTTPS endpoint.\n4. Consumers: Consumers are responsible for reading and processing data from a Kinesis stream. Consumers can be any application that can read data from an HTTP/HTTPS endpoint.", "role": "assistant" } ]	What are the main components of AWS Kinesis?
creative_writing	[ { "content": "From a 10-year old child's perspective, write a short summary of a visit to the Rijksmuseum for the Vermeer exhibition.", "role": "user" }, { "content": "I went to the Rijksmuseum with my mom and dad to see the Vermeer exhibition. Vermeer was a painter who lived a long time ago and he painted really cool pictures. We saw a lot of paintings of people and things from a long time ago. Some of them were really big and some were really small. My favorite painting was one of a girl with a pearl earring. She looked so pretty and I wanted to take her home with me! We also got to see some other paintings by different artists and they were all really pretty too. It was a really fun day and I learned a lot about art!", "role": "assistant" } ]	From a 10-year old child's perspective, write a short summary of a visit to the Rijksmuseum for the Vermeer exhibition.
brainstorming	[ { "content": "What are some of the most popular card games?", "role": "user" }, { "content": "- Poker\n- Bridge\n- Blackjack\n- Rummy\n- Crazy Eights\n- Spades\n- Hearts\n- War\n- Solitaire", "role": "assistant" } ]	What are some of the most popular card games?
closed_qa	[ { "content": "In 1941, a young Catholic priest, José María Arizmendiarrieta settled in Mondragón, a town with a population of 7,000 that had not yet recovered from the poverty, hunger, exile, and tension of the Spanish Civil War. In 1943, Arizmendiarrieta established a technical college which became a training ground for managers, engineers and skilled labour for local companies, and primarily for the co-operatives. What did José María Arizmendiarrieta do?", "role": "user" }, { "content": "José María Arizmendiarrieta was a Catholic Preist who settled in Mondragón, a town with a population of 7,000 that had not yet recovered from the poverty, hunger, exile, and tension of the Spanish Civil War.", "role": "assistant" } ]	In 1941, a young Catholic priest, José María Arizmendiarrieta settled in Mondragón, a town with a population of 7,000 that had not yet recovered from the poverty, hunger, exile, and tension of the Spanish Civil War. In 1943, Arizmendiarrieta established a technical college which became a training ground for managers, engineers and skilled labour for local companies, and primarily for the co-operatives. What did José María Arizmendiarrieta do?
information_extraction	[ { "content": "The Battle of Kressenbrunn (Hungarian: Első morvamezei csata / kroissenbrunni csata) was fought in July 1260 near Groissenbrunn in Lower Austria between the Kingdom of Bohemia and the Kingdom of Hungary for the possession of the duchies of Austria and Styria. The Bohemian forces were led by King Ottokar II Přemysl, while the Hungarians were led by his cousin, King Béla IV of Hungary .\n\nIn 1251, Ottokar's father King Wenceslaus I of Bohemia had not only granted him the title of a Margrave of Moravia, but also installed him as duke of Austria and Styria, territories that were princeless after the ruling Babenberg dynasty had become extinct in 1246. To legitimate his succession, Ottokar in 1252 married the Duchess Margaret of Austria, the sister of the last Babenberg duke and about 26 years his senior. Which two kings fought at the Battle of Kressenbrunn according to the text?", "role": "user" }, { "content": "King Ottokar II and King Béla IV", "role": "assistant" } ]	The Battle of Kressenbrunn (Hungarian: Első morvamezei csata / kroissenbrunni csata) was fought in July 1260 near Groissenbrunn in Lower Austria between the Kingdom of Bohemia and the Kingdom of Hungary for the possession of the duchies of Austria and Styria. The Bohemian forces were led by King Ottokar II Přemysl, while the Hungarians were led by his cousin, King Béla IV of Hungary . In 1251, Ottokar's father King Wenceslaus I of Bohemia had not only granted him the title of a Margrave of Moravia, but also installed him as duke of Austria and Styria, territories that were princeless after the ruling Babenberg dynasty had become extinct in 1246. To legitimate his succession, Ottokar in 1252 married the Duchess Margaret of Austria, the sister of the last Babenberg duke and about 26 years his senior. Which two kings fought at the Battle of Kressenbrunn according to the text?
closed_qa	[ { "content": "Fernando António Nogueira Pessoa (Portuguese: [fɨɾˈnɐ̃du pɨˈsoɐ]; 13 June 1888 – 30 November 1935) was a Portuguese poet, writer, literary critic, translator, publisher, and philosopher, described as one of the most significant literary figures of the 20th century and one of the greatest poets in the Portuguese language. He also wrote in and translated from English and French.\n\nPessoa was a prolific writer, and not only under his own name, for he created approximately seventy-five others, of which three stand out, Alberto Caeiro, Álvaro de Campos, and Ricardo Reis. He did not call them pseudonyms because he felt that this did not capture their true independent intellectual life and instead called them heteronyms. These imaginary figures sometimes held unpopular or extreme views.\n\nPessoa's earliest heteronym, at the age of six, was Chevalier de Pas. Other childhood heteronyms included Dr. Pancrácio and David Merrick, followed by Charles Robert Anon, a young Englishman who became Pessoa's alter ego. In 1905/7, when Pessoa was a student at the University of Lisbon, Alexander Search took the place of Anon. The main reason for this was that, although Search was English, he was born in Lisbon, as was his author. But Search represents a transition heteronym that Pessoa used while searching to adapt to the Portuguese cultural reality. After the republican revolution, in 1910, and consequent patriotic atmosphere, Pessoa created another alter ego, Álvaro de Campos, supposedly a Portuguese naval and mechanical engineer, who was born in Tavira, hometown of Pessoa's ancestors, and graduated in Glasgow. Translator and literary critic Richard Zenith notes that Pessoa eventually established at least seventy-two heteronyms. According to Pessoa himself, there are three main heteronyms: Alberto Caeiro, Álvaro de Campos and Ricardo Reis. Pessoa's heteronyms differ from pen names, because they possess distinct biographies, temperaments, philosophies, appearances, writing styles and even signatures. Thus, heteronyms often disagree on various topics, argue and discuss with each other about literature, aesthetics, philosophy, etc. Who were Fernando Pessoa's main heteronyms?", "role": "user" }, { "content": "Fernando Pessoa created approximately seventy-five heteronyms, of which three stand out, Alberto Caeiro, Álvaro de Campos, and Ricardo Reis.\nPessoa's heteronyms differ from pen names, because they possess distinct biographies, temperaments, philosophies, appearances, writing styles and even signatures.", "role": "assistant" } ]	Fernando António Nogueira Pessoa (Portuguese: [fɨɾˈnɐ̃du pɨˈsoɐ]; 13 June 1888 – 30 November 1935) was a Portuguese poet, writer, literary critic, translator, publisher, and philosopher, described as one of the most significant literary figures of the 20th century and one of the greatest poets in the Portuguese language. He also wrote in and translated from English and French. Pessoa was a prolific writer, and not only under his own name, for he created approximately seventy-five others, of which three stand out, Alberto Caeiro, Álvaro de Campos, and Ricardo Reis. He did not call them pseudonyms because he felt that this did not capture their true independent intellectual life and instead called them heteronyms. These imaginary figures sometimes held unpopular or extreme views. Pessoa's earliest heteronym, at the age of six, was Chevalier de Pas. Other childhood heteronyms included Dr. Pancrácio and David Merrick, followed by Charles Robert Anon, a young Englishman who became Pessoa's alter ego. In 1905/7, when Pessoa was a student at the University of Lisbon, Alexander Search took the place of Anon. The main reason for this was that, although Search was English, he was born in Lisbon, as was his author. But Search represents a transition heteronym that Pessoa used while searching to adapt to the Portuguese cultural reality. After the republican revolution, in 1910, and consequent patriotic atmosphere, Pessoa created another alter ego, Álvaro de Campos, supposedly a Portuguese naval and mechanical engineer, who was born in Tavira, hometown of Pessoa's ancestors, and graduated in Glasgow. Translator and literary critic Richard Zenith notes that Pessoa eventually established at least seventy-two heteronyms. According to Pessoa himself, there are three main heteronyms: Alberto Caeiro, Álvaro de Campos and Ricardo Reis. Pessoa's heteronyms differ from pen names, because they possess distinct biographies, temperaments, philosophies, appearances, writing styles and even signatures. Thus, heteronyms often disagree on various topics, argue and discuss with each other about literature, aesthetics, philosophy, etc. Who were Fernando Pessoa's main heteronyms?
information_extraction	[ { "content": "Titanic is a 1997 American epic romance and disaster film directed, written, produced, and co-edited by James Cameron. Incorporating both historical and fictionalized aspects, it is based on accounts of the sinking of the RMS Titanic and stars Kate Winslet and Leonardo DiCaprio as members of different social classes who fall in love aboard the ship during its ill-fated maiden voyage. The film also features Billy Zane, Kathy Bates, Frances Fisher, Gloria Stuart, Bernard Hill, Jonathan Hyde, Victor Garber, and Bill Paxton.\n\nCameron's inspiration for the film came from his fascination with shipwrecks; he felt a love story interspersed with the human loss would be essential to convey the emotional impact of the disaster. Production began on September 1, 1995, when Cameron shot footage of the actual Titanic wreck. The modern scenes on the research vessel were shot on board the Akademik Mstislav Keldysh, which Cameron had used as a base when filming the wreck. Scale models, computer-generated imagery, and a reconstruction of the Titanic built at Baja Studios were used to re-create the sinking. The film was co-financed by Paramount Pictures and 20th Century Fox; the former handled distribution in North America while the latter released the film internationally. It was the most expensive film ever made at the time, with a production budget of $200 million. Filming took place from July 1996 to March 1997.\n\nUpon its release on December 19, 1997, Titanic achieved significant critical and commercial success, and then received numerous accolades. It was praised for its visual effects, performances (particularly DiCaprio, Winslet, and Stuart), production values, Cameron's direction, musical score, cinematography, story, and emotional depth. Nominated for 14 Academy Awards, it tied All About Eve (1950) for the most Oscar nominations, and won 11, including the awards for Best Picture and Best Director, tying Ben-Hur (1959) for the most Oscars won by a single film. With an initial worldwide gross of over $1.84 billion, Titanic was the first film to reach the billion-dollar mark. It remained the highest-grossing film of all time until Cameron's next film, Avatar, surpassed it in 2010. A number of re-releases since 1997 have pushed the film's worldwide total to $2.249 billion, making it the second film to gross more than $2 billion worldwide (after Avatar). It was also selected for preservation in the United States National Film Registry in 2017 for being \"culturally, historically or aesthetically significant\". Which was the first film to reach he billion-dollar mark?", "role": "user" }, { "content": "With an initial worldwide gross of over $1.84 billion, Titanic was the first film to reach the billion-dollar mark. Upon its release on December 19, 1997, Titanic achieved significant critical and commercial success, and then received numerous accolades. It was praised for its visual effects, performances (particularly DiCaprio, Winslet, and Stuart), production values, Cameron's direction, musical score, cinematography, story, and emotional depth. It was nominated for 14 Academy Awards, and won 11, including the awards for Best Picture and Best Director.", "role": "assistant" } ]	Titanic is a 1997 American epic romance and disaster film directed, written, produced, and co-edited by James Cameron. Incorporating both historical and fictionalized aspects, it is based on accounts of the sinking of the RMS Titanic and stars Kate Winslet and Leonardo DiCaprio as members of different social classes who fall in love aboard the ship during its ill-fated maiden voyage. The film also features Billy Zane, Kathy Bates, Frances Fisher, Gloria Stuart, Bernard Hill, Jonathan Hyde, Victor Garber, and Bill Paxton. Cameron's inspiration for the film came from his fascination with shipwrecks; he felt a love story interspersed with the human loss would be essential to convey the emotional impact of the disaster. Production began on September 1, 1995, when Cameron shot footage of the actual Titanic wreck. The modern scenes on the research vessel were shot on board the Akademik Mstislav Keldysh, which Cameron had used as a base when filming the wreck. Scale models, computer-generated imagery, and a reconstruction of the Titanic built at Baja Studios were used to re-create the sinking. The film was co-financed by Paramount Pictures and 20th Century Fox; the former handled distribution in North America while the latter released the film internationally. It was the most expensive film ever made at the time, with a production budget of $200 million. Filming took place from July 1996 to March 1997. Upon its release on December 19, 1997, Titanic achieved significant critical and commercial success, and then received numerous accolades. It was praised for its visual effects, performances (particularly DiCaprio, Winslet, and Stuart), production values, Cameron's direction, musical score, cinematography, story, and emotional depth. Nominated for 14 Academy Awards, it tied All About Eve (1950) for the most Oscar nominations, and won 11, including the awards for Best Picture and Best Director, tying Ben-Hur (1959) for the most Oscars won by a single film. With an initial worldwide gross of over $1.84 billion, Titanic was the first film to reach the billion-dollar mark. It remained the highest-grossing film of all time until Cameron's next film, Avatar, surpassed it in 2010. A number of re-releases since 1997 have pushed the film's worldwide total to $2.249 billion, making it the second film to gross more than $2 billion worldwide (after Avatar). It was also selected for preservation in the United States National Film Registry in 2017 for being "culturally, historically or aesthetically significant". Which was the first film to reach he billion-dollar mark?
information_extraction	[ { "content": "Electronics deals with electrical circuits that involve active electrical components such as vacuum tubes, transistors, diodes, sensors and integrated circuits, and associated passive interconnection technologies. The nonlinear behaviour of active components and their ability to control electron flows makes digital switching possible, and electronics is widely used in information processing, telecommunications, and signal processing. Interconnection technologies such as circuit boards, electronics packaging technology, and other varied forms of communication infrastructure complete circuit functionality and transform the mixed components into a regular working system.\nToday, most electronic devices use semiconductor components to perform electron control. The underlying principles that explain how semiconductors work are studied in solid state physics, whereas the design and construction of electronic circuits to solve practical problems are part of electronics engineering. How do electronic devices perform electron control?", "role": "user" }, { "content": "Most electronic devices use semiconductor components to perform electron control.", "role": "assistant" } ]	Electronics deals with electrical circuits that involve active electrical components such as vacuum tubes, transistors, diodes, sensors and integrated circuits, and associated passive interconnection technologies. The nonlinear behaviour of active components and their ability to control electron flows makes digital switching possible, and electronics is widely used in information processing, telecommunications, and signal processing. Interconnection technologies such as circuit boards, electronics packaging technology, and other varied forms of communication infrastructure complete circuit functionality and transform the mixed components into a regular working system. Today, most electronic devices use semiconductor components to perform electron control. The underlying principles that explain how semiconductors work are studied in solid state physics, whereas the design and construction of electronic circuits to solve practical problems are part of electronics engineering. How do electronic devices perform electron control?
open_qa	[ { "content": "what are the five pillars of migration or modernization from a legacy data warehouse to a modern lakehouse?", "role": "user" }, { "content": "1. Architecture/infrastructure: Establish the deployment\narchitecture and implement a security and governance\nframework.\n2. Data migration: Map data structures and layout, complete a\none-time load, and finalize an incremental load approach.\n3.ETL and pipelines: Migrate data transformation and\npipeline code, orchestration, and jobs in this phase. Speed\nup your migration by using automation tools and comparing\nyour results with on-premises data and expected results.\n4. Analytics: Repoint reports and analytics for business\nanalytics and business outcomes. Reporting semantic layers\nand online analytics processing (OLAP) cubes should also\nrepoint to the lakehouse via Open Database Connectivity\n(ODBC) and Java Database Connectivity (JDBC).\n5. Data science/machine learning (ML): Establish connectivity\nto ML tools and onboard data science teams.", "role": "assistant" } ]	what are the five pillars of migration or modernization from a legacy data warehouse to a modern lakehouse?
brainstorming	[ { "content": "What should I get for my friends who love to cook?", "role": "user" }, { "content": "Some thoughtful gifts for the avid home cooks include a sous vide, a nice skillet, a beautiful spatula, or a dutch oven. On a budget? You can consider unique condiments such as nice olive oil, chili crunch or spicy mayo.", "role": "assistant" } ]	What should I get for my friends who love to cook?
open_qa	[ { "content": "What is ChatGPT?", "role": "user" }, { "content": "ChatGPT is a large language model (LLM) built by a company names OpenAI. It has the ability to answer in a human like way to any question that you ask it. It can generate code from text, write stories, answer questions, make hashtags, help summarize notes, etc. It was launched on November 30, 2022 and it gained millions of users in the first week it was available for free use by the public. ChatGPT models can also be customized for industry specific use cases using smaller training datasets.", "role": "assistant" } ]	What is ChatGPT?
general_qa	[ { "content": "What is the best way to relax?", "role": "user" }, { "content": "Some of the best ways of relaxing include getting out into nature or a big local park, disconnecting from technology, taking a warm bath with some muscle relaxing salts, making a relaxing drink like a herbal tea or warm milk with honey, spending time with pets, doing something creating or doing some yoga, practicing meditation or mindfulness, getting a massage or trying aromatherapy, writing a journal, listening to relaxing music, focusing on your breathing, visualizing yourself somewhere relaxing or going into a sauna.", "role": "assistant" } ]	What is the best way to relax?
open_qa	[ { "content": "What is the Shiba Inu (crypto)?", "role": "user" }, { "content": "Shiba Inu token (ticker: SHIB) is a decentralized cryptocurrency created in August 2020 by an anonymous person or group known as \"Ryoshi\". It is named after the Shiba Inu (柴犬), a Japanese breed of dog originating in the Chūbu region, the same breed that is depicted in Dogecoin's symbol, itself originally a satirical cryptocurrency based on the Doge meme. Shiba Inu has been characterized as a \"meme coin\" and a pump-and-dump scheme.", "role": "assistant" } ]	What is the Shiba Inu (crypto)?
classification	[ { "content": "Which is a bird or fish: Red snapper or Red kite", "role": "user" }, { "content": "Red kit is a bird, Red snapper is a fish", "role": "assistant" } ]	Which is a bird or fish: Red snapper or Red kite
classification	[ { "content": "Identify which instrument is string or percussion: Cabasa, Huqin", "role": "user" }, { "content": "Huqin is string, Cabasa is percussion.", "role": "assistant" } ]	Identify which instrument is string or percussion: Cabasa, Huqin
brainstorming	[ { "content": "Give me 5 great landmarks to visit in the western united states", "role": "user" }, { "content": "- The Grand Canyon\n- Mount Rainier\n- The Golden Gate Bridge\n- Yellow Stone National Park\n- Disney Land", "role": "assistant" } ]	Give me 5 great landmarks to visit in the western united states