ddp26

9 ms·

91.
by ddp26 7mo ago
Prediction markets are interesting when they are predicting future things nobody knows for sure. "Predicting" private, known information is the wrong use case.
92.
by ddp26 8mo ago
This has persisted for a crazy long time. It's one thing to ship your org chart, it's another thing to leave it in prod for years! Reminds me of the YouTube Music vs Google Play Music debacle.
93.
by ddp26 8mo ago
I tried using wolfram alpha as a tool for an llm research agent, and I couldn't find any tasks it could solve with it, that it couldn't solve with just Google and Python.
94.
I ran 10,000 web research agents(everyrow.io)
12 points by ddp26 8mo ago|0 comments
95.
by ddp26 8mo ago
How do you manage the laptop + mouse?
96.
by ddp26 9mo ago
Yep! We have lots of examples like that where two vendors, or two customers, are completely non-matching. With LLMs and LLM web agents, you also can associate things that are not the same entity. One example we have is merging a table of co
97.
How LLM agents solve the table merging problem(futuresearch.ai)
29 points by ddp26 9mo ago|3 comments
98.
Forecasting the 2026 AI Winner(futuresearch.ai)
2 points by ddp26 9mo ago|1 comments
99.
by ddp26 10mo ago
Because of unprofitability? ARR and growth are very high, and margins are either good or can soon become good. Is the claim that coding agents can't be profitable?
100.
by ddp26 11mo ago
This whole blog post is seemingly about Google, not about the user. "Why We Built Antigravity" etc. "We want Antigravity to be the home base for software development in the era of agents" - cool, why would I as the user
101.
by ddp26 11mo ago
One interesting finding in Stockfisher data is that a lot of these business pivots are actually planned by managers years in advance, in their 10-K and 10-Q filings. Yes, managers are not good forecasters. But they do get certain things rig
102.
by ddp26 11mo ago
Constant iteration, mostly! The most interesting aspect of this is backtesting. Quant models get run on past data to see if their predictions work. When you use LLMs agents, though, you run into their memorized knowledge of the world. And t
103.
Show HN: Stockfisher –– our automated Warren Buffett
16 points by ddp26 11mo ago|4 comments
104.
by ddp26 11mo ago
I agree, but it's funny to think that Project Chauffeur (as it was known then) was doing completely driverless freeway circuits in the bay area as far back as 2012! Back when they couldn't do the simplest things with traffic light
105.
by ddp26 11mo ago
Hi Parag, congrats on the launch. We'll try this out at FutureSearch. I agree there is a need for such APIs. Using Google or Bing isn't enough, and Exa and Brave haven't clearly solved this yet.
106.
by ddp26 1y ago
And to actually answer your question: > Why would Karpathy's view be different for AI and non-AI-experts? For people who understand AI, they can engage with the substance of his claims, about reinforcement learning, continuous learn
107.
by ddp26 1y ago
Hi, author here, sorry I was unclear. This article does make more sense if you've listened to the Dwarkesh podcast linked, and read AI 2027 as was linked. I realize now that it was presumptuous to assume people had done both of these t
108.
by ddp26 1y ago
This seems as good a place as any for a mini obituary. I'm 6 years older than Danya, and we shared the same beloved chess coach in the Bay Area. I played him in a tournament game when I was 17 and he was 11, at the Mechanics Club in SF
109.
The Karpathy Interview, 6 Months After AI 2027(futuresearch.ai)
38 points by ddp26 1y ago|24 comments
110.
by ddp26 1y ago
Predicted by the AI 2027 team in early April: > Mid 2025: Stumbling Agents The world sees its first glimpse of AI agents. Advertisements for computer-using agents emphasize the term “personal assistant”: you can prompt them with tasks li
111.
by ddp26 1y ago
What's the base rate of human therapists giving dangerous advice? Whole schools, e.g. psychotherapy, are possibly net dangerous. If journalists got transcripts and did followups they would almost certainly uncover egregiously bad thera
112.
by ddp26 1y ago
I analyzed OpenAI API profitability in summer 2024 and found inference for gpt-4 class models likely pretty profitable, ~50% gross margins (ignoring capex for training models): https://futuresearch.ai/openai-api-profit
113.
by ddp26 1y ago
I've been involved in prediction markets for a while, and this story highlights why I'm now more optimistic about using AI than crowdsourcing humans. So much, possibly the vast majority, of intellectual energy that goes into predi
114.
by ddp26 2y ago
A lot of commenters here are reacting only to the narrative, and not the Research pieces linked at the top. There is some very careful thinking there, and I encourage people to engage with the arguments there rather than the stylized narrat
115.
by ddp26 2y ago
The story isn't about OpenAI, they say the company could be Xai, Anthropic, Google, or another.
116.
by ddp26 2y ago
Check out the sidebar - they expect tens of thousands of copies of their agents collaborating. I do agree they don't fully explore the implications. But they do consider things like coordination amongst many agents.
117.
by ddp26 2y ago
The forecasts under "Research" are distributions, so you can compare the 10th percentile vs 90th percentile. Their research is consistent with a similar story unfolding over 8-10 years instead of 2.
118.
by ddp26 2y ago
Check out the Timelines Forecast under "research". They model this very carefully. (They could be wrong, but this isn't a guess, it's a well-researched forecast.)
119.
by ddp26 2y ago
John Giannandrea (JG) was running the Google Assistant when I was there. That didn't go so well. (Pre-LLM assistants as a category have done badly - Alexa/Siri did _ok_ but presumably everyone working on them had higher hopes.) I
120.
by ddp26 2y ago
[One of the authors here] I see another post on the front page right now [1] that covers Apple's "secure enclaves". We didn't look much into this, but when we presented our analysis in an event last summer, an audience m

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