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Introducing deep research
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- usaar333 2y agoOverall impressive. Though, the jump for Gaia relative to SOTA is relatively not that high. Especially given that this is o3
- tucnak 2y agoLook, who's copying who now. They added _the_ button!
- blackeyeblitzar 2y agoI’m not sure I understand what you mean by “the button”. If you’re comparing this to DeepSeek’s copying, it’s not really the same thing right? DeepSeek essentially stole intellectual property by violating OpenAI’s terms of service. As I understand it, this is a copy of Google’s Deep Research
- lompad 2y agoDeepseek proved that there is no moat. Thus no path to profitability for openai, anthropic & co. Stealing from thieves is fine by me. Sama was the one claiming that all information could be used to train LLMs, without permisdion of the copyright holders. Now the same is being done to openai. Well, too bad.
- blackeyeblitzar 2y ago> Stealing from thieves is fine by me. Sama was the one claiming that all information could be used to train LLMs, without permisdion of the copyright holders. OpenAI and other LLMs scraping the internet is probably covered under fair use. DeepSeek’s violation of OpenAI’s terms is pretty clearly a violation of their terms and not legal.
- simion314 2y ago>DeepSeek’s violation of OpenAI’s terms is pretty clearly a violation of their terms and not legal. Here is a new thing you learn today, ToS are not laws, you can ignore any ToS and at worst the company might close your account.
- figers 2y agoDidn't OpenAI steal everyone's data they could consume from the internet? Actively being sued by the NY Times and others for this...
- blackeyeblitzar 2y agoYes those cases will be interesting. By default a lot of copyrighted content may be legal to use for training (in the US but also many other places) under what’s called fair use. The cases you’re referring to will likely reinforce this, but it isn’t known yet. Note that it’s not just OpenAI on that side of the argument but also other (non tech) organizations that believe protecting fair use here is current law and essential.
- therealpygon 2y agoCare to explain how something that cannot be copyrighted and was not generated by a human is “intellectual property“? Or are you just parroting a narrative?
- blackeyeblitzar 2y agoTrade secrets are protected by the law. It doesn’t require copyright.
- therealpygon 2y agoExplain the trade secrets contained in non-copyrightable AI outputs and the reasonable efforts OpenAI takes to keep its AI output “secret”. Or are you confused about what a “trade secret” actually is?
- caspper69 2y agoI chuckle every time I see this. Poor OpenAI. Meanwhile, their entire training corpus was the result of scraping the intellectual property and copyrighted materials of THE ENTIRE PUBLIC INTERNET. Woe is them to be sure.
- blackeyeblitzar 2y agoOpenAI’s scraping will likely be ruled as fair use.
- tomrod 2y agoI'm not sure if this is worth a subscription. DSPy and DeepseekR1 can already move this direction, if I understand right.
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- kenjackson 2y agoIf it has access to play by play data for all sports this could be an absolute playground for amateur sports statisticians. The possibilities…
- rvz 2y agoIt appears that OpenAI is in panic mode after the release of DeepSeek. Before they were confident in competing against Google on any AI model they release. Now they are scrambling against open-source after their disastrous operator demonstration and using this deep research demo as cover. Nothing that Google or Perplexity could not already do themselves. By the end of them month, this feature is going be added by a bunch of other open-source projects and this feature won't be as interesting very quickly.
- blackeyeblitzar 2y agoI don’t think you’re comparing the right things here. This feature is more like Google’s Deep Research, which basically goes off and does a whole lot of search and compute to produce something more like a full research report. This has nothing to do with open weight models like DeepSeek (note: DeepSeek, Llama, etc are NOT open source). This feature doesn’t just require the research on the model but also enormous compute. Plus anyone using such a feature for real work is not going to be using DeepSeek or whatever, but a product with trustworthy practices and guarantees.
- rvz 2y ago> This feature is more like Google’s Deep Research, which basically goes off and does a whole lot of search and compute to produce something more like a full research report. Of course. It is in response to their disastrous operator demo which did not justify the $200 per month ChatGPT Pro subscription on top of the release of DeepSeek to make matters worse for them. > This has nothing to do with open weight models like DeepSeek (note: DeepSeek, Llama, etc are NOT open source). It obviously does. Even before they rushed this presentation, they made o3-mini available for ChatGPT free users so it in direct response to DeepSeek. > This feature doesn’t just require the research on the model but also enormous compute. Plus anyone using such a feature for real work is not going to be using DeepSeek or whatever, but a product with trustworthy practices and guarantees. Nothing that Perplexity + DeepSeek-R1 can already do. So what is your point?
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- PartiallyTyped 2y agoI feel that a lot of this can already be achieved via aider (not affiliated), and any of the top models.
- tmnvdb 2y agoDo you have any benchmarks to back up your 'feelings'?
- PartiallyTyped 2y agoI really don't like the snarky tone of the parent comment. Nonetheless, I don't think this is even something that can easily be benchmarked. I'd recommend you take a look at aider [1], and consider how I drew similarities between it and what's presented here. Has ClosedAI presented any benchmarks / evaluation protocols? [1] https://aider.chat/ https://aider.chat/
- tmnvdb 2y agoYes, they show benchmarks in the article linked here. Did you not read it?
- PartiallyTyped 2y agoI don’t think you actually read it. The benchmarks are in reference to the model that’s underlying deep-research, and not deep-research itself. For the latter, they have anecdata from scientists.
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- DigitalSea 2y agoNot sure if people picked up on it, but this is being powered by the unreleased o3 model. Which might explain why it leaps ahead in benchmarks considerably and aligns with the claims o3 is too expensive to release publicly. Seems to be quite an impressive model and the leading out of Google, DeepSeek and Perplexity.
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- xbmcuser 2y agoIt was expensive as they wanted to charge more for it but deepseek has forced their hand
- Sparkyte 2y agoRightfully so, some models are getting super efficient.
- willy_k 2y agoThey’ve only released o3-mini, which is a powerful model but not the full o3 that is being claimed as too expensive to release. That being said, DeepSeek for sure forced their hand to release o3-mini to the public.
- shawabawa3 2y agoo3 mini was previewed in December. Deepseek maybe made them release it a few weeks early but it was already on its way
- sdesol 2y agoI guess the question is, did DeepSeek force them to rethink pricing? It's crazy how much cheaper it (v3 and R1) is, but considering they (Deepseek) can't keep up with demand, the price is kind of moot right now. I really do hope they get the hardware to support the API again. The v3 and R1 models that are hosted by others are still cheap compared to the incumbents, but nothing can compete with DeepSeek on price and performance.
- chrismarlow9 2y agoThis smells like when Google released Gemini to have a product in the space.
- lysace 2y agoEh, not really. Google failed to launch first out of internal political dysfunction and then made a crash effort to launch something to counter the first ChatGPT release. I highly doubt that the concerns of internal political commissars were holding up this particular openai release.
- chrismarlow9 2y agoThat's some fancy words friend.
- xnx 2y agoI agree that OpenAI is trying to stay relevant by announcing a lot of have baked products with little to no availability. > when Google released Gemini to have a product in the space. Bard preceded Gemini.
- febin 2y agoIs this "deep research" tool exploiting open knowledge creators, using their work without compensation?
- johnneville 2y agowould it be open knowledge if it required payment to access ?
- scarab92 2y agoAre you exploiting open knowledge creators, using their work without compensation?
- febin 2y agoThe creators are aware that a human is using this, can we say the same for AI, does it have their consent?
- handfuloflight 2y agoThen consent is granted by transitive property because these AI are yielded by humans.
- hnisoss 2y agoYea but guy paying closedai to get "insights" that basically copy-pasted content from my blog is definitely violating my blogs copyright, and in the end no coin comes to me either. What about that?
- handfuloflight 2y agoCould you provide an example where OpenAI outputting verbatim quotes actually constitutes the copyright violation? Because mechanically retrieving relevant quotes seems analogous to grep/search - the copyright status would depend on how downstream users transform and use that content. Like how quoting your blog in a technical analysis or critique is fair use, but wholesale republishing isn't. This suggests the violation occurs at usage time, not retrieval time.
- ldjkfkdsjnv 2y agoSay whatever you want about openAI, they are shipping more than any other company on the planet.
- kortilla 2y agoWhat does that even mean? Treating each iterative model as a new product is not any different than Google changing its search or youtube recommendation algorithm. Different pre-cooked prompts and filters don’t really amount to new products either, despite them being marketed as such. It’s like adobe treating each tool in photoshop as its own product.
- tmnvdb 2y agoHave you even watched the video? This is a new capability and not a trivial one.
- viraptor 2y agoHow do you even compare different companies? I'd say the massive farms ship every year more than OpenAI ever did.
- navigaid 2y agoName one single open source model released by OpenAI since 2020
- YmiYugy 2y agoIf I understood the graphs correctly, it only achieves 20% pass rate on their internal tests. So I have to wait 30min and pay a lot of money just to sift through walls of most likely incorrect text? Unless the possibility of hallucinations is negligible, this is just way too much content to review at once. The process probably needs to be a lot more iterative.
- tmnvdb 2y agoOnly if you are asking questions at the level of a cutting edge benchmark
- rvnx 2y agoThis is one of the actual questions: > In Greek mythology, who was Jason's maternal great-grandfather? https://www.google.com/search?q=In+Greek+mythology%2C+who+was+Jason%27s+maternal+great-grandfather https://www.google.com/search?q=In+Greek+mythology%2C+who+wa...
- tmnvdb 2y agoThis is a hard question for language models since it targets one of their known weaknesses.
- layer8 2y agoUsers don’t care about how hard something is for LLMs if they receive incorrect output.
- andyg_blog 2y agoGreek mythology? But seriously please elaborate for my less educated self.
- tmnvdb 2y agoLLMs often don't do well on tasks that require composition into smaller subtasks. In this case there is a chain of relations that depend on the previous result.
- thefourthchime 2y agoOpenAI has a deep bench. I bet they pushed this out to change the narrative about deepseek
- btown 2y agoAlso named specifically to muddle the SEO for the term "deep." Nothing that OpenAI does is unintentional.
- bbor 2y agoI have never believed a conspiracy theory more instantly. Deep Search vs. DeepSeek is way more than enough to confuse the average layman! Especially when you're googling something you heard about at work a few hours ago, or on Bloomberg TV
- bonoboTP 2y agoYou might as well say that DeepSeek wanted to cause confusion with DeepMind. Deep isn't such a distinguishing name, deep learning has been a buzzword since 2012.
- leonheld 2y agoOh God, this is such an astute observation. I think it worked so well on me that I didn't even think about the "deep" portion initially. Goes to show how effective these things are psychologically.
- adriand 2y agoFeels like only a matter of time before these crawlers are blocked from large swathes of the internet. I understand that they’re already prohibited from Reddit and YouTube. If that spreads, this approach might be in trouble.
- drcode 2y agoI suppose there is an equilibrium, where sites that penalize these types of crawlers will also get less traffic from people reading ai citations, so for many sites the upsides of allowing it will be greater than the downsides.
- bbor 2y agoTBF OpenAI in particular bought access to Reddit. Otherwise yeah this is my main confusion with all of these products, Perplexity being the biggest -- how do you get around the status-quo of refusing access to bots? Just to start off with, there is no Google Search API, and they work hard to make sure headless browsers can't access the normal service. They do say "Currently, deep research can access the open web...", so maybe "open" there implies something significant. Like, "websites that have agreements with OpenAI and/or do not enforce norobot policies".
- wahnfrieden 2y agoClient-side browsers that crawl for users (and prompt for logins or captcha as needed) won't be as easily blockable
- scarab92 2y agoI doubt those crawler rules will be honoured for long. I wouldn’t even be surprised if a law is passed requiring sites to provide equal access to humans whether accessed directly or via these models. It’s too important an innovation to stall, especially considering the US’s competitors (China) won’t respect robots.txt either.
- cj 2y agoAnyone selling anything would want to remain crawlable if people use this to research something that could lead to a purchase.
- reader9274 2y agoI think we're all reaching AI fatigue. Fewer and fewer people care anymore
- rvnx 2y agoEspecially this is not a breakthrough justifying a 340B USD valuation, but rather the work that junior developers can do; implement a loop of Bing Searches connected to an LLM.
- tmnvdb 2y agoPeak HN comment
- rvnx 2y agoDoesn't make it untrue. Agents that can search the internet exist for a while now and have been essentially solved and happily used in platforms like Perplexity. It's really "meh", very far from revolutionary. Keep in mind this company is trying to convince everybody they need 500B USD now (through the Stargate project).
- spyckie2 2y agoTo go from partially automated to fully automated is thousands of non trivial edge cases and unforeseen decision points that must be tamed. To say this is trivial is like saying the one shot ai prompted twitter clone is the same thing as twitter. Peak HN indeed.
- CamperBob2 2y agoLet us know when your Bing-bot scores over 20% on the HLE benchmark.
- rvnx 2y agoIt's literally a browsing agent that searches the internet and they know the questions in advance when preparing the agent Without internet: 10% With internet: 23% In addition: > We found that the ground-truth answers for one dataset were widely leaked online in very small letters, and they blocked these URLs at runtime but not training time. It's not bad, but not revolutionary at all compared to the leap that was GPT-2 from GPT-3, or GPT-4o to DeepSeek-R1
- gwerbret 2y agoTo anyone who's tried it: how does it handle captchas? I can't imagine that OpenAI's IP addresses are anyone's favorites for unfettered access to web properties these days.
- xt00 2y ago"will find, analyze, and synthesize hundreds of online sources" Synthesize? Seems like the wrong word -- I think they would want to say something like, "analyze, and synthesize useful outputs from hundreds of online sources"..
- nicce 2y agoOn the other hand, accurate if it is prone for hallucination…
- tmnvdb 2y agoYou can synthesize the parts to get the whole. Both uses are correct AFAIK
- pjot 2y agoFrom New Oxford dictionary: > combine (a number of things) into a coherent whole: pupils should synthesize the data they have gathered | Darwinian theory has been synthesized with modern genetics.
- tmnvdb 2y agoEating popcorn while the scaling doubters scramble to move the goalposts for the nth time.
- ADeerAppeared 2y agoI'm sorry but what the fuck is this product pitch? Anyone who's done any kind of substantial document research knows that it's a NIGHTMARE of chasing loose ends & citogenesis. Trusting an LLM to critically evaluate every source and to be deeply suspect of any unproven claim is a ridiculous thing to do. These are not hard reasoning systems, they are probabilistic language models.
- timsh 2y agothis is so precise. I guess we’ll need a global version of https://datacolada.org/ https://datacolada.org/ quite soon to not get hit by a bus in every scientific field
- panarky 2y ago> they are probabilistic language models This is like arguing an Airbus cannot possibly fly because it is 165 tonnes of aluminum, steel and plastic. The proof is in the fact that it flies, not what it is constructed from.
- ADeerAppeared 2y ago> The proof is in the fact that it flies, not what it is constructed from. And LLMs do not. > "But it looks like reasoning to me" My condolences. You should go see a doctor about your inability to count the number of 'R's in a word.
- panarky 2y ago"Even though that Airbus looks like it's flying it's really not because my personal definition of 'flying' requires feathers and flapping wings."
- rizky05 2y ago[dead]
- CamperBob2 2y agoOK, what's your next move, now that letter-counting has been solved by the current generation of frontier models? CoT reasoning is reasoning, whether you like it or not. If you don't understand that, it means the models are already smarter than you.
- cye131 2y agoDoes anyone actually have access to this? It says available for pro users on the website today - I have pro via my employer but see no "deep research" option in the message composer.
- greatpostman 2y agoHave pro, can’t see it yet
- snewman 2y agoTwo different people I know with pro subscriptions report not having access yet.
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- fosterfriends 2y agoI have pro, in US, not seeing yet
- _bin_ 2y agowhat about a full refresh of the page or perhaps jump into the dev tools and check "disable cache" could also be aggressive caching from cloudflare. could be they're just trying to announce more stuff to maintain cachet and can't yet support all users forking over 200/month.
- hi_hi 2y agoThis is terrifying. Even though they acknowledge the issues with hallucinations/errors, that is going to be completely overlooked by everyone using this, and then injecting the outputs into their own powerpoints. Management Consulting was bad enough before the ability to mass produce these graphs and stats on a whim. At least there was some understanding behind the scenes of where the numbers came from, and sources would/could be provided. The more powerful these tools become, the more prevelant this effect of seepage will become.
- cyanydeez 2y ago[flagged]
- tmnvdb 2y ago> At least there was some understanding behind the scenes of where the numbers came from, and sources would/could be provided. Oh Sweet summer child.
- opdahl 2y agoHi tmnvdb, since you seem to love these super smart LLMs I thought it would be fun to have openais o3-mini-high analyze your recent comments in contrast to the Hacker News Comment Guidelines. Here is the output it gave me, hope it helps you: ------ Hey, I've noticed a few things in your style that are both strengths and opportunities for improvement: Strengths: - You clearly have deep knowledge and back up your points with solid data and examples. - Your confidence and detailed analysis make your arguments compelling. Opportunities: - At times, your tone can feel a bit combative, which might shut down conversation. - Focusing on critiquing ideas rather than questioning someone's honesty can help keep the discussion constructive. - A clearer structure in longer posts could make your points even more accessible. Overall, your passion and expertise shine through—tweaking the tone a bit might help foster even more productive debates. ------ Just reply here if you want the full 500+ words analysis that goes into more detail.
- autoconfig 2y agoEither you care about being correct or you don't. If you don't care then it doesn't matter whether you made it up or the AI did. If you care then you'll fact check before publishing. I don't see why this changes.
- VerdisQuo5678 2y agoThe accuracy of this tool does not matter. This is exclusively designed for box ticking "reports" that nobody reads and a produced for the sake of itself.
- arbywhy 2y ago99% of corpo upper management slide deck work. ai only makes more of this useless pencil-neck board of directors slop.
- reaperman 2y ago“Pencil-neck” is a strange insult to use here. How are software developers, or hardware design engineers, or finance workers any less “pencil-neck” than “board of directors”?
- tomrod 2y agoThe new term for this is "AI Loopidity", highlighting the unintelligent ouroboros nature of one side using AI to generate content and then another side to consume content.
- sockaddr 2y agoSimilar to “Bullshit jobs” All the AI commercials are designed to appeal to people that don’t produce any actual value but haven’t been detected by the system yet. Need to send email to boss? Press magic button! Job well done, idiot. Someone send you big scary email? Press magic button! Good job dummy! Someone wants to go eat some Italian with you, push magic button for totally not-ad result. Enjoy your Olive Garden, moron.
- rsanek 2y agoi think the apple ads are the poster child here. hopefully we can see more inventive ones than just serving lazy people.
- ldjkfkdsjnv 2y agoSo much cynicism and hate in these comments, especially as we are likely witnessing AGI come to life. Its still early, but it might be coming. Where is the excitement? This is an interesting time to be alive. HN has a huge cultural problem that makes this website almost irrelevant. All the interesting takes have moved to X/twitter
- bonoboTP 2y agoHN is and has always been quite negative/pessimistic/cynical in general. That Dropbox comment was quite a long time ago already.
- roenxi 2y agoWe're looking at trends that may well obliterate the economic value of a well trained human mind sitting behind a keyboard all day. That is a bit of a threat to most people on HN if the trending continues at the current rate and direction.
- rvz 2y ago> "So much cynicism and hate in these comments, especially as we are likely witnessing AGI come to life. Its still early, but it might be coming. Where is the excitement? This is an interesting time to be alive." Maybe you can define what "AGI" really means and what the end-game and the economic implications are when 'AGI" is some-what achieved? OpenAI somehow believes that they haven't achieved "AGI" yet, which they continue to do this on purpose for obvious reasons. The first hint I will give you is that it certainly won't be a utopia.
- layer8 2y ago“May you live in interesting times” is usually taken as a curse. ;) More seriously, it’s unclear why one should be excited by the prospect of AGI, especially when instrumentalized by corporations and authoritarian governments.
- rpcope1 2y ago> especially as we are likely witnessing AGI come to life Man, I've got a great deal on some oceanfront property in Wyoming for you.
- wilg 2y agoI think this looks cool. Apparently unlike everyone else on this website?
- tmnvdb 2y agoHN is full of people who want to feel smart by complaining.
- frontalier 2y agois this you? https://news.ycombinator.com/item?id=42913544 https://news.ycombinator.com/item?id=42913544
- tmnvdb 2y agoGleefully celebrating the defeat of my enemies is not complaining.
- therealmarv 2y agoI don't know. OpenAI is so bad in naming... the average person on the street will confuse Deepseek with Deep Research. Also not to forget o1, o3 ... 4o
- Havoc 2y agoThe descriptions of the product sounded substantially more impressive than the actual samples tbh. Still I think there is a big market for this sort of „go away for 30 mins and figure this out“ style agent
- TechDebtDevin 2y agoThis is 5-10 years out. What OpenAI is displaying here I've been able to do with relatively little code, a bit of scraping and far less capable models for a year. I really don't see what is novel or useful here.
- prng2021 2y ago"Deep research was trained using end-to-end reinforcement learning" Does this mean they skipped supervised fine tuning like DeepSeek did with R1?
- OutOfHere 2y agoNo, it just suggests that RL was used over a base SFT model, and moreover that RL here was tuned to this research task. Personally I don't think that RL is strictly necessary for this task at all, but perhaps it helps.
- layer8 2y agoFrom the demo: “Use bullets and tables where necessary for clarity.” It’s weird that it would be necessary to specify that. I suppose they want to showcase that you can influence the output style, but it’s strange that you’d have to explicitly specify the use of something that is “necessary for clarity”. It comes across as either a flaw in the default execution, or as a merely performative incantation.
- jasonjmcghee 2y agoSurprised more comments aren't mentioning deepseek has this feature (for free) already. Assuming this is why OpenAI scrambled to release it. The examples they have on the page work well on chat.deepseek.com with r1 and search options both enabled. Do I blindly trust the accuracy of either though? Absolutely not. I'm pretty concerned about these models falling into gaming SEO and finding inaccurate facts and presenting them as fact. (How easy is it to fool / prompt inject these models?) But has utility if held right.
- nicce 2y agoI wish Kagi would work with similar performance. Their lenses feature is perfect for this and they already filter out most of the SEO spam based on trackers and other typical red flags.
- starchild3001 2y agoNot really accurate. The "Search" functionality you're describing in DeepSeek is comparable to OpenAI's existing "Search GPT." OpenAI's recent announcement refers to a more advanced capability, similar to Gemini's existing "deep research" feature. DeepSeek's current offerings are significantly more limited in scope.
- jasonjmcghee 2y agoDoesn't seem like access is available to try "deep research" yet on OpenAI, so I can only speak to what I tried, which was their examples on the blog post (using DeepSeek w/ R1 + Search) and results were pretty similar. AFAIK OpenAI's current offering uses 4o, and it does a web search and then pipes it into 4o. I'm guessing adding CoT + other R1/o3 like stuff is one of the key effective differences. But time will tell how different it is. Maybe it's a dramatic improvement.
- WiSaGaN 2y agoSearchGPT is bad because its underlying model is not a reasoning one. Deepseek one mentioned above is closer to deep research than searchgpt.
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- pjs_ 2y agoMcKinsey mode
- sockaddr 2y agoHeh
- TechDebtDevin 2y agoMore like high school intern mode.
- rsanek 2y agodon't be hyperbolic. deep research would need to help cause an opioid crisis for to get to that level.
- spyckie2 2y agoWhy is HN not creating policy against moral prigotry? There is no useful discussion here anymore. Seriously begging the mods to take a closer look, or at least PG to not abandon his curated internet space.
- esafak 2y agopriggery or bigotry? And what are you referring to?
- esafak 2y agoIs there a benchmark we can compare this against You.com's research mode? It looks like R1 forced them to release o3 prematurely and give it Internet access. And they didn't want to say they released o3 so they called it 'Deep Research'.
- spyckie2 2y agoIs this ability really a prerequisite to AGI and ASI? Reasoning, problem solving, research validation - at the fundamental outset it is all refinement thinking. Research is one of those areas where I remain skeptical it is that important because the only valid proof is in the execution outcome, not the compiled answer. For instance you can research all you want about the best vacuum on the internet but until you try it out yourself you are going to be caught in between marketing, fake reviews, influencers, etc. maybe the science fields are shielded from this (by being boring) but imagine medical pharmas realizing that they can get whatever paper to say whatever by flooding the internet with their curated blog articles containing advanced medical “research findings”. At some point you cannot trust the internet at all and I imagine that might be soon. I worry especially with the rapidly changing landscape of the amount of generated text in the internet that research will lose a lot of value due to massive amounts of information garbage. It will be a thing we used to do when the internet was still “real”.
- simonw 2y ago> Is this ability really a prerequisite to AGI and ASI? That depends entirely on how you choose to define "AGI".
- observationist 2y agoIt's a direction in a vast landscape, not a feature of itself - being better at different tasks, like search generally, and research in conjunction with reasoning, gets the model closer to AGI. An AGI will be able to do these tasks - so the point of the research is to have more Venn diagrams of capabilities like these to help narrow down the view on things that might actually be fundamental mechanisms involved in AGI. Moravec detailed the idea of a landscape of human capabilities slowly being submerged by AI capabilities, and the point at which AI can do anything a human can, in practice or in principle, we'll know for certain we've reached truly general AI. This idea includes things like feeling pain and pleasure, planning, complex social, oral, and ethical dynamics, and anything else you can possibly think of as relevant to human intelligence. Deep Research is just another island being slowly submerged by the relentless and relentlessly accelerating flood.
- ejang0 2y agoCan anyone confirm if this is available in Canada and other countries? This site says "We are still working on bringing access to users in the United Kingdom, Switzerland, and the European Economic Area." But I'm not sure about other countries. I don't have Pro currently, only Plus.
- carbocation 2y agoI don't even see it in the US right now.
- carbocation 2y ago(Update: it’s visible for me now.)
- steveridout 2y agoJust use a VPN to pretend you're in the US and it works.
- ejang0 2y agohttps://help.openai.com/en/articles/10500283-deep-research-faq https://help.openai.com/en/articles/10500283-deep-research-f... "Pro users (located outside the UK, Switzerland, and the European Economic Area) have access to 100 deep research tasks per month." So to me that must include Canada, right? I signed up for Pro. There it is. (For future reference, for someone else.)
- 6gvONxR4sf7o 2y agoThere are some people in the blogosphere who are known experts in their niche or even niche-famous because they write popular useful stuff. And there are a ton more people who write useful stuff because they want that 'exposure.' At least, they do in the very broadest sense of writing it for another human to read it. I wonder if these people will keep writing when their readership is all bots. Dead internet here we come.
- seanmcdirmid 2y agoI'm all for writing just for the bots, if I can figure it out. A lot of academic papers aren't really read anyways, just briefly glanced at so they can be cited together, large publications like journal pubs or dissertations even less so. But the ability to add to a world of knowledge that is very easy to access by people who want to use it...that is very appealing to me as an author. No more trudging through a bunch of papers with titles that might be relevant to what I want to know about...and no more trudging through my papers, I'm OK with that.
- lmm 2y agoOf course they will. Loads of people go around taking hundreds of photos with the biggest camera they can afford even though no-one else will ever willingly look at them.
- Bjorkbat 2y agoActually sounds pretty cool, but the graph on expert level tasks is confusing my expectations. Saying it has a pass rate of less than 20% sounds a lot like saying this thing is wrong most of the time. Granted, these strike me as difficult tasks and I’d likely ask it to do far simpler things, but I’m not really sure what to expect from looking at these graphs. Ah, but the fact that it bothers to cite its sources is a huge plus. Between that and its search abilities it sounds valuable to me
- random_cynic 2y agoI think that's mostly because of the access to information it has. Much of the highly useful information is not on the public internet or shows up on search engines, only domain experts know about them. Also, the websites may be paywalled or gated by login. So a better comparison would be if the models had the same level of access as an expert.
- EcommerceFlow 2y agoCan't even get Sunday nights off trying to keep up fml.
- jaco6 2y agoI see lots of warranted skepticism about the capabilities of this tool, but the reality is that this is an incremental step toward full automation of white collar labor. No, it will not make all analysts jobless overnight. But it may reduce hiring of said people by 5 or 10 percent. And as people get better at using the tool and the tool itself gets better, those numbers will grow. Remember that it took decades for the giant pool of typing secretaries in Mad Men to disappear, but they did disappear. Gone forever. Interestingly, anger about the diminishment of secretarial male white collar work in Germany due to the spread of the typewriter a few decades earlier was one of the drivers of the Nazi Party’s popularity (see Evans, the Rise of the Third Reich). AI’s triumph in the white collar workplace will be gradual, not instantaneous. And it will be grimly quiet, because no one likes white collar workers the way they like blue collar workers, for some odd reason, and there’s no tradition of solidarity among white collar workers. Everyone will just look up one day and find that the local Big Corp headquarters is…empty.
- michaelgiba 2y agoGemini has had this for a month or two, also named "Deep Research" https://blog.google/products/gemini/google-gemini-deep-research/ https://blog.google/products/gemini/google-gemini-deep-resea... Meta question: what's with all of the naming overlap in the AI world? Triton (Nvidia, OpenAI) and Gro{k,q} (X.ai, groq, OpenAI) all come to mind
- james_promoted 2y agoI've always thought the Triton situation was intentional since the name isn't generic and because the companies are stepping on each others toes here (Nvidia's Triton simplifying owning your inference; OpenAI's Triton eroding the need for familiarity with CUDA). I couldn't figure out who publicly used the name first though.
- stonogo 2y agoIt's a sort of unofficial trade association where they coalesce on specific redefinitions of terms to meet their sales and PR efforts. First they came for "intelligence," then "open source," then "reason," and it will continue. Any word which the PR wants but they can't achieve gets redefined -- "grok" is a perfect example, since in the original sci-fi book it meant "total understanding." The mythological Triton ruled the deeps, so the "deep learning" sales copy immediately co-opted it.
- albert_e 2y agoAlso "accuracy" as a measure of model's performance used to mean something objective in the traditional ML world. Now with LLMs it is what human evaluators feel about the LLM output?
- pazimzadeh 2y ago> In Nature journal's Scientific Reports conference proceedings from 2012, in the article that did not mention plasmons or plasmonics, what nano-compound is studied? Aren't there more than one articles that did not mention plasmons or plasmonics in Scientific Reports in 2012? Also, did they pay for access to all journal contents? that would be useful
- nicce 2y agoMaybe that is the only one with open access
- getnormality 2y agoThe demo on global e-commerce trends seems less useful than a Google search, where the AI answer will at least give you links to the claimed information.
- jmount 2y agoI had no idea there was a market for "Compile a research report on how the retail industry has changed in the last 3 years. Use bullets and tables where necessary for clarity." I imagine reading such a result is pure torture.
- deleted 2y ago[deleted]
- airstrike 2y ago"Deep research" is now somehow synonymous to searching online for stats and pulling stuff from Statista? And when I want to make changes to that report, do I have to tweak my prompt and get an entirely different document? Not sure if I'm too tired and can't see it but the lack of images/examples of the resulting report in this announcement doesn't inspire a lot of confidence just yet.
- highfrequency 2y agoCan it compile and run (non-Python) code as part of its tool use? Compile-run steps always seemed like they would be a huge value add during reasoning loops - it feels very silly to get output from ChatGPT, try to run it in terminal, get an error and paste the error to have ChatGPT immediately fix it. Surely it should be able to run code during the reasoning loop itself?
- simonw 2y agoIt sounds like it can run Python, which means it has access to Code Interpreter, which means it can run various other languages as well if you can convince it to do so. I've used Code Interpreter to compile and run C code - https://simonwillison.net/2024/Mar/23/building-c-extensions-for-sqlite-with-chatgpt-code-interpreter/ https://simonwillison.net/2024/Mar/23/building-c-extensions-... - and I've managed to get it to run JavaScript (by uploading a Deno binary) and even Lua and PHP in the past as well: https://til.simonwillison.net/llms/code-interpreter-expansions https://til.simonwillison.net/llms/code-interpreter-expansio...
- RayVR 2y agoEach release from openAI gives me less hope for them and this whole AI boom. They should be leading the charge of highlighting how the current generation of LLMs fail, not churning out half-baked overhyped products. Yes, they can do some cool tricks, and tool calling is fun. No one should trust the output of these models, though. The hallucinations are bad, and my experience with the "reasoning" models is that as soon as they fuck up (they always do) they go off the rails worse than the base LLMs.
- nycdatasci 2y agoPro user. No access like everyone else. OpenAI is very much in an existential crisis and their poor execution is not helping their cause. Operator or “deep research” should be able to assume the role of a Pro user, run a quick test, and reliably report on whether this is working before the press release right?
- samplatt 2y agoThat's the third time in this thread you've stated "OpenAI is in an existential crisis". It looks very suspicious.
- nycdatasci 2y agoI thought it was an appropriate response in multiple contexts. If I’m wrong, please provide a rebuttal or counterpoint.
- _bin_ 2y agoman you work for high flyer or something? i know that's not really a fair question but oai still seems to lead the pack. i know it's a hype-y area but responding to one (1) model that's comparable to o4 but cheaper with "guys it's so over for openai" is excessive.
- nycdatasci 2y agoAppreciate the thoughtful engagement. I work for a large, US-based investment firm. No relationship w/ High Flyer. This isn’t a single model. Almost the entire leadership team around sama has left and almost certainly agrees with me on this. OpenAI’s business model is not sustainable.
- resters 2y agoStill not seeing access on my account.
- _bin_ 2y agothey're not giving it to us lowly $20/month users yet :( gotta take out a second mortgage and throw them 200/month if you want it now
- resters 2y agoI have the $200/month version. Deep Research arrived this morning. So far I tried it on one problem and it seems limited by the "front end" being 4o-mini. It ignored most of my initial prompt and also ignored the previous research it asked for which I provided. The final output was high quality and definitely was enriched by the web searching it did, but it left out a crucially important dimension of the problem because it was unable to ingest the background info I provided adequately. I'd like to see a version of it where the front end model is o1-pro
- lolpanda 2y ago"synthesize large amounts of online information" does it heavily depend on the search engine performance and relevance of the search results? I don't see any mention of Google or Bing. Is this using their internal search engine then?
- RandomWorker 2y agoI’m a researcher and honestly not worried. 1. Developing the right question has always been the largest barrier to great research. Not sure OpenAI can develop the right question without the Human experience. The second biggest part of my role is influencing people that my questions are the right questions. Which is made easier when you have a thorough understanding of the first. That being said, I’m sure there will be many people here that will tell me that algorithms already influence people, and ai can think through much of any issues there are. I do use these systems from time to time, but it just never renders any specific information that would make it great research.
- RayVR 2y ago100% agree. These systems serve best at augmenting information discovery. When I'm tackling a new area or looking for the right terminology, these models provide a quick shortcut because they have good probabilistic "understanding" of my naive, jargon-free description. This allows me to pull in all of the jargon for the area of research I'm interested in, and move on to actually useful resources, whether that be journal articles, textbooks, or - rarely - online posts/blogs/videos. the current "meta" is probably something like Elicit + notebookLM + Claude for accelerating understanding of complex topics and extracting useful parts. But, again, each step requires that I am closely involved, from selecting the "correct" papers, to carefully aggregating and grooming the information pulled in from notebookLM, to judging the the usefulness of Claude's attempts to extract what I have asked for
- deleted 2y ago[deleted]
- GeoAtreides 2y ago> Developing the right question has always been the largest barrier to great research. I thought funding was the biggest barrier to great research
- elashri 2y agoIt is actually interesting for people working in academia. I would like to test it but no way I can afford $200/m right now. Can someone test it with this prompt. "As a research assistant with comprehensive knowledge of particle physics, please provide a detailed analysis of next-generation particle collider projects currently under consideration by the international physics community. The analysis should encompass the major proposed projects, including the Future Circular Collider (FCC) at CERN, International Linear Collider (ILC), Compact Linear Collider (CLIC), various Muon Collider proposals, and any other significant projects as of 2024. For each proposal, examine the planned energy ranges and collision types, estimated timeline for construction and operation, technical advantages and challenges, approximate costs, and key physics goals. Include information about current technical design reports, feasibility studies, and the level of international support and collaboration. Present a thorough comparative analysis that addresses technical feasibility, cost-benefit considerations, scientific potential for new physics discoveries, timeline to first data collection, infrastructure requirements, and environmental impact. The projects should be compared in terms of their relative strengths, weaknesses, and potential contributions to advancing our understanding of fundamental physics. Please format the response as a structured technical summary suitable for presentation at a topical meeting of particle physicists. Where appropriate, incorporate relevant figures and tables to facilitate clear comparisons between proposals. Base your analysis on information from peer-reviewed sources and official design reports, focusing on the most current available data and design specifications. Consider the long-term implications of each proposal, including potential upgrade paths, flexibility for future modifications, and integration with existing research infrastructure."
- sagarpatil 2y agoI’ll do it. AFL right now.
- deleted 2y ago[deleted]
- fosterfriends 2y agoRan it for you using o3-high! Here's a link to the results: https://chatgpt.com/share/67a0b227-8ee4-800f-a8ed-882e7bab9740 https://chatgpt.com/share/67a0b227-8ee4-800f-a8ed-882e7bab97... Hopefully helpful, happy to test others for you :) -- Raw output -- Understood. I will conduct a detailed technical analysis of next-generation particle collider projects, focusing on the Future Circular Collider (FCC), International Linear Collider (ILC), Compact Linear Collider (CLIC), Muon Collider proposals, and other significant initiatives. The report will include: - Planned energy ranges and collision types - Estimated construction and operation timelines - Technical advantages and challenges - Approximate costs - Key physics goals - Review of technical design reports and feasibility studies - International collaboration and support - Comparative analysis on feasibility, cost-benefit, scientific potential, infrastructure needs, and environmental impact - Long-term considerations, including upgrade paths and integration with existing facilities The analysis will be formatted as a structured technical summary, suitable for presentation at a topical meeting of particle physicists, with comparative tables and figures where relevant. I will update you when the report is ready. # Next-Generation Particle Collider Projects: A Comparative Technical Analysis ## Introduction High-energy physics is charting plans for new colliders to extend beyond the LHC and its High-Luminosity upgrade (HL-LHC). The discovery of the 125 GeV Higgs boson has motivated proposals for a dedicated “Higgs factory” lepton collider to study its properties with precision, as well as future energy-frontier machines to search for new physics. Several next-generation collider initiatives are under consideration internationally as of 2024. These include CERN’s proposed *Future Circular Collider (FCC)*, Japan’s *International Linear Collider (ILC)*, CERN’s *Compact Linear Collider (CLIC)*, various designs for a *Muon Collider*, China’s *Circular Electron-Positron Collider (CEPC)* and its successor *Super Proton-Proton Collider (SppC)*, among others. Each proposal differs in collision type (electron-positron, proton-proton, muon-muon, etc.), energy scale, technology, timeline, cost, and physics focus. This summary reviews each project’s key parameters – *planned energy ranges, collision types, timeline, technical advantages/challenges, cost, and physics goals* – based on technical design reports and feasibility studies. A comparative analysis then contrasts their *technical feasibility, cost-benefit, scientific potential for discoveries, timeline to first data, infrastructure needs, and environmental impact*, highlighting the relative strengths and weaknesses of each approach. We also discuss long-term implications such as upgrade paths, flexibility for future modifications, and integration with existing infrastructure. (Citations refer to official reports and peer-reviewed sources using the format 【source†lines】.) ## Future Circular Collider (FCC) – CERN - *Type and Energy:* The FCC is a *proposed 100 km circular collider* at CERN that would be realized in stages. The first stage, *FCC-ee*, is an electron-positron ($e^+e^-$) collider with center-of-mass energy tunable from ~90 GeV up to 350–365 GeV, covering the Z boson pole, WW threshold, Higgs production (240 GeV), and top-quark pair threshold (~350 GeV). A second stage, *FCC-hh*, would use the same tunnel for a proton-proton collider at up to *100 TeV* center-of-mass energy (an order of magnitude above the LHC’s 14 TeV). Heavy-ion collisions (e.g. Pb–Pb) are also envisioned. An *FCC-eh* option (electron-hadron collisions) is considered by adding a high-energy electron injector to collide with the proton beam. This integrated FCC program thus spans both *precision lepton* collisions and *energy-frontier hadron* collisions. - *Timeline:* The conceptual schedule foresees *FCC-ee construction in the 2030s* and a start of operations by around *2040* (as the LHC/HL-LHC program winds down). According to the FCC Conceptual Design Report, an $e^+e^-$ Higgs factory could begin delivering physics in ~2040, running for 15–20 years. The *hadron collider FCC-hh* would be constructed subsequently (using the same tunnel and upgraded infrastructure), aiming for *first proton-proton collisions in the late 2050s】. This staged approach (lepton collider first, hadron later) mirrors the successful *LEP–LHC sequence*, leveraging the $e^+e^-$ machine to produce great precision data (and to build infrastructure) before pushing to the highest energies with the hadron machine. ... (Too long for HN to write more)
- rajnathani 2y agoI remember about 10-15 years ago that Ray Kurzweil (who still works at Google) or someone at Google had this idea for what Google should be able to do: About doing deep research by itself with a simple search query. I can't find the source. Obviously it didn't pan out without transformers.
- corentin88 2y agoCurious about the use cases here. Building AI Agents? But which one?
- picografix 2y agoI think deep research as a service could be a really strong use case for enterprises, as long as they have access to non-public data. I assume that most of this guarded data is high quality, and seeing progress in these areas might end up being even more impressive than it is now.
- lngnmn2 2y ago[dead]
- lngnmn2 2y ago[dead]
- anon373839 2y agoSetting aside how well it works, I think this is a pretty nice demonstration of how to do UX for an agentic RAG app. I like that the intermediate steps have been pushed out to a sidebar, with updates that both provide some transparency about the process and make the high latency more palatable.
- auggierose 2y agoThe flow reminds me a bit of undermind.ai.
- rob_c 2y agoFeels more and more like openAI doesn't have "that next big thing". To be clear I'm constantly impressed with what they have and what I get as a customer, but the delivery since 4 hasn't exactly been in line with Altman's Musk-tier vapoware promises...
- gorgoiler 2y agoFor “deep research” I’m also reading “getting the answers right”. Most people I talk to are at the point now where getting completely incorrect answers 10% of the time — either obviously wrong from common sense, or because the answers are self contradictory — undermines a lot of trust in any kind of interaction. Other than double checking something you already know, language models aren’t large enough to actually know everything. They can only sound like they do. What I’m looking for is therefore not just the correct answer, but the correct answer in an amount of time that’s faster than it would take me to research the answer myself, and also faster than it takes me to verify the answer given by the machine. It’s one thing to ask a pupil to answer an exam paper to which you know the answers. It’s a whole next level to have it answer questions to which you don’t know the answers, and on whose answers you are relying to be correct.
- sandos 2y agoI mean this all falls down due to the need of verification: "Limitations Deep research unlocks significant new capabilities, but it’s still early and has limitations. It can sometimes hallucinate facts in responses or make incorrect inferences" How do I know which parts are false? It will take as long to verify as to research!
- wnurmi 2y ago[dead]
- igleria 2y agoIt's really worrying to me, even as a self proclaimed "LLM <-> AI" skeptic, to see what kind of stuff people pretend to get out from an LLM. Typewriter monkeys as a service almost. Still useful for the odd task here and there, but not as useful as all the money being invested in this (except for the companies getting that money, that is). edit: actual example of something I'd expect a real AI to be able to solve by itself, but currently LLMs fail miserably https://x.com/RadishHarmers/status/1885884032220643587 https://x.com/RadishHarmers/status/1885884032220643587
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- taran_narat 2y agoisn't this just perplexity?
- gigatexal 2y agoOk so I do this as a noob in some field. How do I know or trust the research conclusions? How do I know it’s not hallucinated its conclusions? I’ll likely have to do my own research to just verify it and then if I did I might as well have done the research myself.
- freehorse 2y agoI love that when "open"ai releases things last year or so, they do not actually release them. So we get the chance in the meantime to all enjoy a bunch of speculative, shilling comments here about this next great thing being miles ahead of competitors/close to AGI/the tool that will actually do X thing that others complain so far llms are failing to do.
- dazzaji 2y agoLate Sunday night, I gained access to OpenAI’s newly launched Deep Research and immediately tested it on a draft blog post about Uniform Electronic Transactions Act (UETA) compliance and AI-agent error handling [1]. Here’s what I found: Within minutes, it generated a detailed, well-cited research report that significantly expanded my original analysis, covering: * Legal precedents & case law interpretations (including a nuanced breakdown of UETA Section 10). * Comparative international frameworks (EU, UK, Canada). * Real-world technical implementations (Stripe’s AI-driven transaction handling). * Industry perspectives & business impact (trust, risk allocation, compliance). * Emerging regulatory standards (EU AI Act, FTC oversight, ISO/NIST AI governance). What stood out most was its ability to: - Synthesize complex legal, business, and technical concepts into clear, actionable insights. - Connect legal frameworks, industry trends, and real-world case studies. - Maintain a business-first focus, emphasizing practical benefits. - Integrate 2024 developments with historical context for a deeper analysis. The depth and coherence of the output were comparable to what I would expect from a team of domain experts—but delivered in a fraction of the time. From the announcement: Deep Research leverages OpenAI’s next-generation model, optimized for multi-step research, reasoning, and synthesis. It has already set new performance benchmarks, achieving 26.6% accuracy on Humanity’s Last Exam (the highest of any OpenAI model) and a 72.57% average accuracy on the GAIA Benchmark, demonstrating advanced reasoning and research capabilities. Currently available to Pro users (with up to 100 queries per month), it will soon expand to Plus and Team users. While OpenAI acknowledges limitations—such as occasional hallucinations and challenges in source verification—its iterative deployment strategy and continuous refinement approach are promising. My key takeaway: This LLM agent-based tool has the potential to save hours of manual research while delivering high-quality, well-documented outputs. Automating tasks that traditionally require expert-level investigation, it can complete complex research in 5–30 minutes (just 6 minutes for my task), with citations and structured reasoning. I don’t see any other comments yet from people who have actually used it, but it’s only been a few hours.I’d love to hear how it’s performing for others. What use cases have you explored? How did it do? (Note: This review is based on a single use case. I’ll provide further updates as I conduct broader testing.) [1] https://www.dazzagreenwood.com/p/ueta-and-llm-agents-a-deep-dive-into https://www.dazzagreenwood.com/p/ueta-and-llm-agents-a-deep-...
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- Xuban 2y agoThis make sense, I often use the normal search feature to research a very large ammount of information and it mostly does not work well. If the new search feature increases the number of websites scrapped and the pertinence of the websites, I'm all in.
- timabdulla 2y agoI just gave it a whirl. Pretty neat, but definitely watch out for hallucinations. For instance, I asked it to compile a report on myself (vain, I know.) In this 500-word report (ok, I'm not that important, I guess), it made at least three errors. It stated that I had 47,000 reputation points on Stack Overflow -- quite a surprise to me, given my minimal activity on Stack Overflow over the years. I popped over to the link it had cited (my profile on Stack Overflow) and it seems it confused my number of people reached (47k) with my reputation, a sadly paltry 525. Then it cited an answer I gave on Stack Overflow on the topic of monkey-patching in PHP, using this as evidence for my technical expertise. Turns out that about 15 years ago, I _asked_ a question on this topic, but the answer was submitted by someone else. Looks like I don't have much expertise, after all. Finally, it found a gem of a quote from an interview I gave. Or wait, that was my brother! Confusingly, we founded a company together, and we were both mentioned in the same article, but he was the interviewee, not I. I would say it's decent enough for a springboard, but you should definitely treat the output with caution and follow the links provided to make sure everything is accurate.
- giarc 2y agoWhat's faster? Writing a 500 word report "from scratch" by researching the topic yourself, vs. having AI write it then having to fact check every answer and correct each piece manually? This is why I don't use AI for anything that requires a "correct" answer. I use it to re-write paragraphs or sentences to improve readability etc, but I stop short of trusting any piece of info that comes out from AI.
- mdp2021 2y ago> Then it cited an answer I gave on Stack Overflow [...] using this as evidence for my technical expertise. Turns out that about 15 years ago, I _asked_ a question on this topic, but the answer was submitted by someone else Artificial dementia... Some parties are releasing products much earlier than the ability to ship well working products (I am not sure that their legal cover will be so solid), but database aided outputs should and could become a strong limit to that phenomenon of remembering badly. Very linearly, like humans: get an idea, then compare it to the data - it is due diligence and part of the verification process in reasoning. It is as if some moves outside linear pure product progress reasoning are swaying the RnD towards directions outside the primary concerns. It's a form of procrastination.
- smusamashah 2y agocan sometimes hallucinate facts in responses or make incorrect inferences, though at a notably lower rate than existing ChatGPT models, according to internal evaluations. It may struggle with distinguishing authoritative information from rumors, and currently shows weakness in confidence calibration, often failing to convey uncertainty accurately Taken from the limitations section. These tools are just good at creating pollution. I don't see the point of delegating a (not just) research where 1% blatant mistakes are acceptable. These need much better grounding before handing out to masses. I can not take any output by these tools (google summaries, comment summaries by amazon, youtube summaries etc etc) while knowing for a fact some of that is a total lie. I can not tell which part is a lie. e.g. If LLM says that in any given text the sentiment is divided, it could be just one person with an opposing view. If same task was given to a person, I could reason with that person on any conclusion. These tools will reason on their hallucinations.
- joanfihu 2y agoThere is no way I'll read all that text from the demos... AskPandi has a similar feature called "Super Search" that essentially checks more sources and self validates it's own answers. iT's AgEnTic. The answers are easier to digest, if you search for products, you'll get a list of products with images, prices and retailers.
- monkeydust 2y agoWhat a decent setup to replicate via open model and agent framework? One thing I have struggled with is getting comprehensive web searches using an agentic framework.
- regularjack 2y agoOf course, they had to weasel the word "deep" in there.
- sharpshadow 2y agoAre they launching a new feature after some other AI got the attention to get the attention back?
- titzer 2y agoIt's great that none of these AI models are being foisted on us by advertising companies.
- rcdwealth 2y ago[dead]
- axpy906 2y agoDon’t most researchers have a local setup plugged into Olama so that they do NOT share their search information?
- sivm 2y agoI used it once to research language learning and had my pro mode taken away pending review for abuse.
- Alifatisk 2y agoWhen I saw new to llms, I used Bing ai in a fun way. So when I was writing my report, it was sometimes hard to find discussions or material about a certain topic. What I did was to ask Bing ai about that topic and it returned information aswell as sources to where it found those, so I picked up all those links and researched them myself. Bing ai was a great resource for finding relevant links, this was until I found out about perplexity, my life haven't been the same since.
- throwaway123lol 2y agoThis is so lame. This feels like another desperate attempt to stay relevant cobbled together after the DeepSeek announcement last week. What was the other attempt they made? Skip a version number to seem like more progress was made (o1->o3)? From what I can tell "o3" is just the same as o1 with an extra reasoning-effort parameter. Oh and "Deep research" is available to people on the $200 per month plan? Lol - cool. I've been using DeepSeek a lot more recently and it's so incredibly good even with all the scaling issues.
- z7 2y agoBusiness and technical analysis of DeepSeek's entire R&D history with extrapolations: https://chatgpt.com/share/67a0d59b-d020-8001-bb88-dc9869d52b2e https://chatgpt.com/share/67a0d59b-d020-8001-bb88-dc9869d52b...
- DoctorOetker 2y agoWould formalizing Wiles' proof of Fermat's Last Theorem be considered deep research? Is it able to formalize it in say metamath's set.mm? Or is the position of OpenAI that Wiles' proof is incomplete?
- DoctorOetker 2y agoah yes, when you get downvoted for asking Questions, not even Claims.
- bilater 2y agoNot quite the agent they are building but I have an open source alternative that lets you use a variety of models, based on links of your choice to generate reports: https://github.com/btahir/open-deep-research https://github.com/btahir/open-deep-research
- TheGradfather 2y agoThe OpenAI Deep Research graph showing tool calls vs pass rate reveals something fascinating about how these models handle increasing amounts of information. The relationship follows a logistic curve that plateaus around 16% pass rate, even as we allow more tool calls. This plateau behavior reflects something deeper about our current approach to AI. We've built transformer architectures partly inspired by simplified observations of human cognition - particularly how our brains use attention mechanisms to filter and process information. And like human attention, these models have inherent constraints: each attention layer normalizes scores to sum to 1, creating a fixed "attention budget" that must be distributed across all inputs. A recent paper (https://arxiv.org/abs/2501.19399 https://arxiv.org/abs/2501.19399) explores this limitation, showing how standard attention becomes increasingly diffuse with longer contexts. Their proposed "Scalable-Softmax" helps maintain focused attention at longer ranges, but still shows diminishing returns - pushing the ceiling higher rather than eliminating it. But here's the deeper question: As we push toward AGI and potentially superintelligent systems, should we remain bound by architectures modeled on our current understanding of human cognition? The human brain's limited attention mechanism evolved under specific constraints and for specific purposes. While it's remarkably effective for human-level intelligence, it might be fundamentally limiting for artificial systems that could theoretically process information in radically different ways. Looking at the Deep Research results through this lens, the plateau might not just be a technical limitation to overcome, but a sign that we need to fundamentally rethink how artificial systems could process and integrate information. Instead of trying to stretch the capabilities of attention-based architectures, perhaps we need to explore entirely different paradigms of information processing that aren't constrained by biological analogues. This isn't to dismiss the remarkable achievements of transformer architectures, but rather to suggest that the path to AGI might require breaking free from some of our biologically-inspired assumptions. What would an architecture that processes information in ways fundamentally different from human cognition look like? How might it integrate and reason about information without the constraints of normalized attention? Would love to hear thoughts from others working on these problems, particularly around novel approaches that move beyond our current biological inspirations.
- enknamel 2y agoSo they did a RAG on the whole internet? Basically Google search results summary but better?
- teleforce 2y agoWhat a coincident of releasing deep research for your product when one of your main competitors has DeepSeek R1 as their best performant version /s Seriously, for the past 20+ years it's hard to imagine doing research without Google platform namely Google Search, Scholar, Patent and Book, but now it seems agent AI based on LLM is the way to. In twenty years in the future it will be hard to imagine that doing research without them. But as many people already pointed out Google probably the best company by far to perform this emerging AI based research. In data eco-system terms (refer to any book on data engineering), Google has already perform has the most important data preparation and data engineering upstream activities including data ingestion and transformation. Now given their vast amount of processed data they can just serve it to downstream data analytics or AI for performing research with minimum error/hallucinations as possible. According to Google there is no moat for any companies against open source LLM, but if any company that can has the moat it will be Google itself.
- gqgs 2y agoIf I'm understanding this correctly it sounds functionally similar to the report generating project Standard released a few weeks ago [1]. [1] https://storm.genie.stanford.edu/ https://storm.genie.stanford.edu/
- littlestymaar 2y agoThere's an open source version of this that you can use with local LLMs: https://www.reddit.com/r/LocalLLaMA/comments/1gvlzug/i_created_an_ai_research_assistant_that_actually/ https://www.reddit.com/r/LocalLLaMA/comments/1gvlzug/i_creat... In fact, it's been three month since the release and I wouldn't even be surprised if OpenAI took inspiration from it.
- jakobschwich 2y ago[dead]
- martin82 2y agoThey reduce one expensive but mostly useless gimmick after the other. No one if ever going to trust the output this generates and then needs to spend so much time fact checking that they might as well do the entire research from scratch themselves...