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Introducing deep research

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Re: Introducing deep research

#241

Post by alvah »

rvnx wrote: post #83
tmnvdb wrote: post #57

Earlier quoted context omitted.

Peak HN comment

Doesn'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).

I haven’t tried the OpenAI version yet, as I’m on their peasant-level $20 plan, but the Google equivalent is way superior to Perplexity (I use both extensively). The web search Perplexity carries out is superficial compared to the Google product; it misses a large percentage of what Gemini Deep Research finds, and for a particular task in my business this makes a huge difference.

Re: Introducing deep research

#242

Post by nimithryn »

_bin_ wrote: post #228
andyg_blog wrote: post #121

Earlier quoted context omitted.

Greek mythology? But seriously please elaborate for my less educated self.

it tests syllogistic reasoning: Jason's mother was Tyro, whose father was Poesidon, whose father was Kronos. it also tests whether it "eagerly" rather than comprehensively considers something: a maternal great-grandfather could be the father of either one's maternal grandmother or maternal grandfather. so the answer could also be king Aeolus of the Etruscans. ideally a model would be able to answer this accurately an…

I think there are more possible answers? Jason's mother differs depending on the author...

For example, Jason's mother was Philonis, daughter of Mestra, daughter of Daedalion, son of Hesporos. So Jason's maternal great-grandfather was Hesporos.

Re: Introducing deep research

#243

Post by sagarpatil »

elashri wrote: post #240

It 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 t…

I’ll do it. AFL right now.

Re: Introducing deep research

#244

Post by xendipity »

bbor wrote: post #45
DigitalSea wrote: post #15

Not 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.

Interesting, thanks for highlighting! Did not pick up on that. Re:"leading", tho: Effectiveness in this task environment is well beyond the specific model involved, no? Plus they'd be fools (IMHO) to only use one size of model for each step in a research task -- sure, o3 might be an advantage when synthesizing a final answer or choosing between conflicting sources, but there are many, many steps required to get to th…

I don't believe we have any indication that the big offerings (claude.ai, Gemini, operator, tasks, canvas, chatgpt) use multiple models in one call (other than for different modalities like having Gemini create an image). It seems to actually be very difficult technically and I'm curious as to why.

I wonder how much of an impact our being still so early in the productization phase of this all is. Like it takes a ton of work and training and coordination to get multiple models synced up into an offering and I think the companies are still optimizing for getting new ideas out there rather truly optimizing them.

Re: Introducing deep research

#245

Post by RainyDayTmrw »

autoconfig wrote: post #89
hi_hi wrote: post #56

This 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 w…

Either 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.

It's possible that you care, but the person next to you doesn't, and external pressures force you to keep up with the person who's willing to shovel AI slop. Most of us don't have a complete luxury of the moral high ground at our jobs.

Re: Introducing deep research

#246

Post by toomim »

michaelgiba wrote: post #183

Gemini has had this for a month or two, also named "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

John Stewart had something to say about this: https://youtu.be/Byg8VZdKK88?si=pX1WbtRwZCBGpwHS&t=141

Re: Introducing deep research

#247

Post by doomroot »

RainyDayTmrw wrote: post #245
autoconfig wrote: post #89

Earlier quoted context omitted.

Either 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.

It's possible that you care, but the person next to you doesn't, and external pressures force you to keep up with the person who's willing to shovel AI slop. Most of us don't have a complete luxury of the moral high ground at our jobs.

It looks like the moral high just came more in demand.

Re: Introducing deep research

#248

Post by sadeshmukh »

petra wrote: post #85
kevlened wrote: post #66

Earlier quoted context omitted.

It's more likely this is a response to Gemini Deep Research released in December https://blog.google/products/gemini/google-gemini-deep-resea...

That Google product isnt that good, it can't really replace research done by a person.

Nobody was going to hire a researcher for a quick question.

Re: Introducing deep research

#249

Post by panarky »

ADeerAppeared wrote: post #164
panarky wrote: post #94

Earlier quoted context omitted.

> 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.

> 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.

"Even though that Airbus looks like it's flying it's really not because my personal definition of 'flying' requires feathers and flapping wings."

Re: Introducing deep research

#250

Post by shihab »

michaelgiba wrote: post #183

Gemini has had this for a month or two, also named "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

From the creator of Triton (OpenAI)-

"PS: The name Triton was coined in mid-2019 when I released my PhD paper on the subject. I chose not to rename the project when the "TensorRT Inference Server" was rebranded as "Triton Inference Server" a year later since it's the only thing that ties my helpful PhD advisors to the project."

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