投稿時間:2024-06-14 06:05:55 RSSフィード2024-06-14 06:00分まとめ(8件)

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IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] オフィス環境が「やる気」に直結？　働く環境に満足する社員の約9割が「仕事がおもしろい」	https://www.itmedia.co.jp/business/articles/2406/14/news040.html	itmedia,オフィス,オンライン	2024-06-14 05:45:00
海外TECH	Engadget	House of the Dragon renewed for season 3 ahead of season 2 premiere	https://www.engadget.com/house-of-the-dragon-renewed-for-season-3-ahead-of-season-2-premiere-203425819.html?src=rss	HBO has announced that House of the Dragon will be back for a third season The network confirmed the renewal of the Game of Thrones spinoff series in a press release just three days ahead of its Season premiere George R R Martin Ryan Condal and the rest of our incredible executive producers cast and crew have reached new heights with the phenomenal second season of House of the Dragon Francesca Orsi executive vice president of HBO Programming and head of HBO Drama Series and Films said in the press release HBO hasn t revealed any details about the third season of House of the Dragon nor has it given a release window Still it s not uncommon in the streaming era for networks like HBO to renew shows for future seasons before upcoming seasons go live like The Last of Us Last year Orsi told Deadline that House of the Dragon may have more than four seasons She added that Martin whose book Fire amp Blood inspired the spin off series and showrunner Condal were going to discuss where to end the show before the writers strike started That strike ended on September with the Writers Guild of America reaching an agreement on protections against generative AI The renewal also comes two days after Martin confirmed in a blog post that HBO is moving forward with another Game of Thrones spin off Ten Thousand Ships He wrote that playwright Eboni Booth is working on a new pilot for the prequel about Queen Nymeria and the Rhoynar after the show was previously scrapped This article originally appeared on Engadget at	2024-06-13 20:34:25
海外TECH	Engadget	If AI is going to take over the world, why can't it solve the Spelling Bee?	https://www.engadget.com/if-ai-is-going-to-take-over-the-world-why-cant-it-solve-the-spelling-bee-170034469.html?src=rss	My task for our AI overlords was simple help me crack the New York Times Spelling Bee I had spent a large chunk of a Saturday evening trying to shape the letters G Y A L P O and N into as many words as possible But three hours points and words ーincluding nonapology lagoon and analogy ーlater I had hit a wall A few more words was all I needed to propel myself into Spelling Bee s genius echelon the title reserved for those who unscramble percent of all possible words using the given letters and the point at which the puzzle considers itself effectively solved percent solvers are bestowed the rank of queen bee but even I have limits My human mind was clearly struggling but this task seemed like child s play for AI so I fired up ChatGPT told it I was trying to win the Spelling Bee gave it my letters and laid out the rules Give me a list of every word that can be formed with them I typed You re allowed to repeat letters but each word must contain N When I hit enter this is what ChatGPT spat back Here is a list of words formed with the letters G Y A L P O N that must contain the letter N GLNPAYOYPNLPGNOYLONAPYLGLGNAPYOANLYNAYGOPLGYPONAOGPLNYPNAOGLYThis is just a sample of the list due to the extensive number of permutations possible Not a great start The words need to be in the dictionary I typed back Sure came the response I ll provide a list of valid English words based on the given letters ANGLY GALON LANG Clearly this wasn t working so I turned to Microsoft s Copilot YANG PLAYING PLANNING ANNOYINGLY Google s Gemini GAPON GON GIAN and Anthropic s Claude MANGO ONGOING LAWN LAY Meta AI helpfully told me that it made sure to only include words that are recognized by dictionaries in a list that contained NALYP and NAGY while Perplexity ーa chatbot with ambitions of killing Google Search ーsimply wrote GAL hundreds of times before freezing abruptly Perplexity a chatbot with ambitions of killing Google Search went to pieces when asked to form words from a set of letters Screenshot by Pranav Dixit EngadgetAI can now create images video and audio as fast as you can type in descriptions of what you want It can write poetry essays and term papers It can also be a pale imitation of your girlfriend your therapist and your personal assistant And lots of people think it s poised to automate humans out of jobs and transform the world in ways we can scarcely begin to imagine So why does it suck so hard at solving a simple word puzzle The answer lies in how large language models the underlying technology that powers our modern AI craze function Computer programming is traditionally logical and rules based you type out commands that a computer follows according to a set of instructions and it provides a valid output But machine learning of which generative AI is a subset is different It s purely statistical Noah Giansiracusa a professor of mathematical and data science at Bentley University told me It s really about extracting patterns from data and then pushing out new data that largely fits those patterns OpenAI did not respond on record but a company spokesperson told me that this type of feedback helped OpenAI improve the model s comprehension and responses to problems Things like word structures and anagrams aren t a common use case for Perplexity so our model isn t optimized for it company spokesperson Sara Platnick told me As a daily Wordle Connections Mini Crossword player I m excited to see how we do Microsoft and Meta declined to comment Google and Anthropic did not respond by publication time At the heart of large language models are transformers a technical breakthrough made by researchers at Google in Once you type in a prompt a large language model breaks down words or fractions of those words into mathematical units called tokens Transformers are capable of analyzing each token in the context of the larger dataset that a model is trained on to see how they re connected to each other Once a transformer understands these relationships it is able to respond to your prompt by guessing the next likely token in a sequence The Financial Times has a terrific animated explainer that breaks this all down if you re interested I thought I was giving the chatbots precise instructions to generate my Spelling Bee words all they were doing was converting my words to tokens and using transformers to spit back plausible responses It s not the same as computer programming or typing a command into a DOS prompt said Giansiracusa Your words got translated to numbers and they were then processed statistically It seems like a purely logic based query was the exact worst application for AI s skills akin to trying to turn a screw with a resource intensive hammer The success of an AI model also depends on the data it s trained on This is why AI companies are feverishly striking deals with news publishers right now ーthe fresher the training data the better the responses Generative AI for instance sucks at suggesting chess moves but is at least marginally better at the task than solving word puzzles Giansiracusa points out that the glut of chess games available on the internet almost certainly are included in the training data for existing AI models I would suspect that there just are not enough annotated Spelling Bee games online for AI to train on as there are chess games he said If your chatbot seems more confused by a word game than a cat with a Rubik s cube that s because it wasn t especially trained to play complex word games said Sandi Besen an artificial intelligence researcher at Neudesic an AI company owned by IBM Word games have specific rules and constraints that a model would struggle to abide by unless specifically instructed to during training fine tuning or prompting If your chatbot seems more confused by a word game than a cat with a Rubik s cube that s because it wasn t especially trained to play complex word games None of this has stopped the world s leading AI companies from marketing the technology as a panacea often grossly exaggerating claims about its capabilities In April both OpenAI and Meta boasted that their new AI models would be capable of reasoning and planning In an interview OpenAI s chief operating officer Brad Lightcap told the Financial Times that the next generation of GPT the AI model that powers ChatGPT would show progress on solving hard problems such as reasoning Joelle Pineau Meta s vice president of AI research told the publication that the company was hard at work in figuring out how to get these models not just to talk but actually to reason to plan to have memory My repeated attempts to get GPT o and Llama to crack the Spelling Bee failed spectacularly When I told ChatGPT that GALON LANG and ANGLY weren t in the dictionary the chatbot said that it agreed with me and suggested GALVANOPY instead When I mistyped the world sure as sur in my response to Meta AI s offer to come up with more words the chatbot told me that sur was indeed another word that can be formed with the letters G Y A L P O and N Clearly we re still a long way away from Artificial General Intelligence the nebulous concept describing the moment when machines are capable of doing most tasks as well as or better than human beings Some experts like Yann LeCun Meta s chief AI scientist have been outspoken about the limitations of large language models claiming that they will never reach human level intelligence since they don t really use logic At an event in London last year LeCun said that the current generation of AI models just do not understand how the world works They re not capable of planning They re not capable of real reasoning he said We do not have completely autonomous self driving cars that can train themselves to drive in about hours of practice something a year old can do Giansiracusa however strikes a more cautious tone We don t really know how humans reason right We don t know what intelligence actually is I don t know if my brain is just a big statistical calculator kind of like a more efficient version of a large language model Perhaps the key to living with generative AI without succumbing to either hype or anxiety is to simply understand its inherent limitations These tools are not actually designed for a lot of things that people are using them for said Chirag Shah a professor of AI and machine learning at the University of Washington He co wrote a high profile research paper in critiquing the use of large language models in search engines Tech companies thinks Shah could do a much better job of being transparent about what AI can and can t do before foisting it on us That ship may have already sailed however Over the last few months the world s largest tech companies Microsoft Meta Samsung Apple and Google have made declarations to tightly weave AI into their products services and operating systems The bots suck because they weren t designed for this Shah said of my word game conundrum Whether they suck at all the other problems tech companies are throwing them at remains to be seen How else have AI chatbots failed you Email me at pranav dixit engadget com and let me know Update June PM ET This story has been updated to include a statement from Perplexity This article originally appeared on Engadget at	2024-06-13 20:19:10
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