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After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster... show more

Diogo Almeida

30,903 subscribers

5,397,295 次观看 • 6 小时前 •via X (Twitter)

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47 条评论

Diogo Almeida 的头像

Diogo Almeida6 小时前

The gains aren’t free: Jev can't generate text Comparing Jev vs LLMs side-by-side makes the trade-off clear Fun fact: replacing sequential computation with parallel is the same way Transformers leapfrogged RNNs

Diogo Almeida 的头像

Diogo Almeida6 小时前

We believe that the future is code + AI, so made workflow evals to reflect that Jev costs: $42 / BILLION input tokens ($0.042 / MTok) and output tokens are free (forever - they’re too cheap to meter with our new architecture) Jev is named after Jevons paradox and off the intelligence per $ charts

Diogo Almeida 的头像

Diogo Almeida6 小时前

We love how this doomo doomonstrates real-time intelligence and what can be doone with code + AI! ~10 calls/sec = ~$7/hour

Diogo Almeida 的头像

Diogo Almeida6 小时前

Game: race from one Wikipedia page to another using only links Challenge: choosing between hundreds to thousands of links Shows not just intelligence-per-second, but also the compounding benefits of not hallucinating with high-cardinality choices

Diogo Almeida 的头像

Diogo Almeida6 小时前

Extraordinary claims require extraordinary evidence so check out our release blog for more technical info: Join our waitlist for early access: Have technical chats and meme with us on Discord (rumors are good memers skip the line): We are so pumped this is in the hands of developers now, and we are just getting started!!!

Diogo Almeida 的头像

Diogo Almeida6 小时前

absolutely yes to "smart if statements", or as the old school would put it "neuro-symbolic AI"!

Damian Player 的头像

Damian Player6 小时前

only the start!

TypeSafe AI 的头像

TypeSafe AI6 小时前

hello world

Ihtesham Ali 的头像

Ihtesham Ali6 小时前

All of wanted something like this but did not know who is going to build it and actually ship it. This is amazing. I am excited for this project.

Diogo Almeida 的头像

Diogo Almeida6 小时前

<3 we've seen a lot of people want something like this - since the first days of InstructGPT / LangChain

Muhammad Ayan 的头像

Muhammad Ayan6 小时前

400x cheaper would make some CFOs refresh twice 👀

Diogo Almeida 的头像

Diogo Almeida6 小时前

that's the hope! our experience is that any savings >10x means basically free for users, and anything above that means "this is so cheap who knows where else we can throw intelligence"

Daniel Smidstrup 的头像

Daniel Smidstrup6 小时前

Seems almost too cheap, definitely worth exploring

Diogo Almeida 的头像

Diogo Almeida6 小时前

we can charge more if it's too cheap 😬

CG 的头像

CG6 小时前

20-400x cheaper is crazy 👀

Markandey Sharma 的头像

Markandey Sharma6 小时前

This could be especially useful for agents and automated workflows.

Wall St Engine 的头像

Wall St Engine6 小时前

👀

Aaliya 的头像

Aaliya6 小时前

awesome The parallel computation angle is fascinating — it shows how much architecture matters for real-time AI performance.

Dania 的头像

Dania6 小时前

Composable intelligence optimized for decisions is fascinating.

Amit 的头像

Amit6 小时前

Really curious to see how Jev performs in real world decision tasks.

Ayush 的头像

Ayush6 小时前

Next day content creators: you're using jev wrong

Diogo Almeida 的头像

Diogo Almeida6 小时前

😭 plz let us know if our docs have issues 🙏

Not Elon Musk 的头像

Not Elon Musk6 小时前

Keep pushing forward, humans thank you…

Zara 的头像

Zara6 小时前

T40-400x cheaper could change AI economics.

Diogo Almeida 的头像

Diogo Almeida6 小时前

going all in on Jevons Paradox!!!

Manish Kumar Shah 的头像

Manish Kumar Shah6 小时前

This is a really interesting shift from generating text to making decisions that software can act on.

Jaynit Makwana 的头像

Jaynit Makwana6 小时前

the Wikipedia race is a great benchmark idea. hundreds of choices per step is closer to real agent workloads than any leaderboard I've seen.

Diogo Almeida 的头像

Diogo Almeida6 小时前

games are an incredible way to both show (1) the limitations of LLMs (too slow to be in the gameplay) and (2) the advantages of intelligence-per-second

Ayush 的头像

Ayush6 小时前

How can it help regular individuals without a tech background??

Hari 的头像

Hari6 小时前

Congrats on the launch!

klöss 的头像

klöss6 小时前

someone is cooking

George Wing 的头像

George Wing6 小时前

great collection of shirts

Diogo Almeida 的头像

Diogo Almeida6 小时前

this one is my favorite ☺️

Ayush 的头像

Ayush6 小时前

This could be revolutionary

vas 的头像

vas6 小时前

👀

Rony 的头像

Rony6 小时前

is the cost advantage mainly coming from training, inference, or both?

Diogo Almeida 的头像

Diogo Almeida6 小时前

a little bit of both! you can see in the side-by-side video that inference is massively more efficient with parallel generation. the long-term advantage will be with training though! we believe the approach to lead to a much less jagged frontier

Gina Acosta 的头像

Gina Acosta6 小时前

love this. builders can try more approaches without burning budget

Dae 的头像

Dae6 小时前

bro what happened to pacing the frontier 😭

Diogo Almeida 的头像

Diogo Almeida6 小时前

the frontier isn't reliable enough to automate though 😭

Dae 的头像

Dae6 小时前

are you saying my vibecoded vertical harness isn't reliable????

Santiago 的头像

Santiago6 小时前

I really like that the model returns a confidence score. That alone can reduce a ton of hallucinations because we can decide whether to present a response to a user or pass it to a HIL. What I'm curious to understand is whether those confidence scores are actually accurate or are calibrated in any way.

Liam | AI Tools & News 的头像

Liam | AI Tools & News6 小时前

Free output tokens completely changes the cost equation.

Diogo Almeida 的头像

Diogo Almeida6 小时前

no reasoning tokens either 😉

Morteza 的头像

Morteza6 小时前

Goat! 20x faster and 40x cheaper is a serious claim guys great job

Calira 的头像

Calira6 小时前

This changes the AI economics game.

Vyom 的头像

Vyom6 小时前

Awesome!!!

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309,800 次观看 • 11 天前

From rewriting Google’s search stack in the early 2000s to reviving sparse trillion-parameter models and co-designing TPUs with frontier ML research, Jeff Dean has quietly shaped nearly every layer of the modern AI stack. As Chief AI Scientist at Google and a driving force behind Gemini, Jeff has lived through multiple scaling revolutions from CPUs and sharded indices to multimodal models that reason across text, video, and code. We sat down with Jeff to unpack what it really means to “own the Pareto frontier,” why distillation is the quiet force behind every generation of faster, cheaper models, how energy not FLOPs is becoming the true constraint on AI compute, what it takes to co-design hardware and models 2–6 years into the future, why unified multimodal systems will outperform specialized ones, what it was like leading the charge to unify all of Google’s AI teams, and his prediction that deeply personalized models with access to your full digital context will redefine what useful AI looks like. Jeff Dean Google DeepMind Google

From rewriting Google’s search stack in the early 2000s to reviving sparse trillion-parameter models and co-designing TPUs with frontier ML research, Jeff Dean has quietly shaped nearly every layer of the modern AI stack. As Chief AI Scientist at Google and a driving force behind Gemini, Jeff has lived through multiple scaling revolutions from CPUs and sharded indices to multimodal models that reason across text, video, and code. We sat down with Jeff to unpack what it really means to “own the Pareto frontier,” why distillation is the quiet force behind every generation of faster, cheaper models, how energy not FLOPs is becoming the true constraint on AI compute, what it takes to co-design hardware and models 2–6 years into the future, why unified multimodal systems will outperform specialized ones, what it was like leading the charge to unify all of Google’s AI teams, and his prediction that deeply personalized models with access to your full digital context will redefine what useful AI looks like. Jeff Dean Google DeepMind Google

Latent.Space

529,014 次观看 • 7 个月前

Today is a big day at Odyssey. We're sharing Explorer, our first generative world model. We think world models are the next frontier for AI, enabling wonderful new things. To help shape this, Ed Catmull, the iconic founder of Pixar, is joining our board and investing.

Today is a big day at Odyssey. We're sharing Explorer, our first generative world model. We think world models are the next frontier for AI, enabling wonderful new things. To help shape this, Ed Catmull, the iconic founder of Pixar, is joining our board and investing.

Odyssey

75,333 次观看 • 1 年前

Today, we're launching Vals Public Sector: independent AI evaluation for government. Recent events have made one thing clear: the government has a stake in understanding how frontier AI models perform on day-to-day work, and the risks they carry. This work is central to who we are. We've spent years building industry-leading benchmarks alongside the top AI labs and enterprise domain experts. Now, we’re bringing that same rigor to support government where AI matters most, from public benefits to national security. We are excited for the work ahead!

Today, we're launching Vals Public Sector: independent AI evaluation for government. Recent events have made one thing clear: the government has a stake in understanding how frontier AI models perform on day-to-day work, and the risks they carry. This work is central to who we are. We've spent years building industry-leading benchmarks alongside the top AI labs and enterprise domain experts. Now, we’re bringing that same rigor to support government where AI matters most, from public benefits to national security. We are excited for the work ahead!

Vals AI

10,956 次观看 • 2 个月前

“but after that [10 shows in Vegas], i will not see you for an incredibly long time… i just need a rest. i’ve spent the last 7 years building the life for myself, I want to live it now. I want to live my new life I’ve been building” — Adele

“but after that [10 shows in Vegas], i will not see you for an incredibly long time… i just need a rest. i’ve spent the last 7 years building the life for myself, I want to live it now. I want to live my new life I’ve been building” — Adele

fran sainz⁵⁵🍷

788,990 次观看 • 2 年前

Today I'm excited to introduce Hark, a new artificial intelligence lab building the most advanced, personal intelligence in the world We've been in stealth for 8 months, assembling one of the greatest AI and hardware teams on the planet I want to explain why I started Hark and what we're focused on I've spent the last 3 years working on the hardest AI challenge imaginable: giving AI a humanoid body. On the digital side, I've been using all the existing LLM chatbots - and I have to say, they feel incredibly dumb to me AGI, in the limit, should feel like a sci-fi movie. It should be able to listen and talk. It should have persistent memory and be highly personalized. It should see and touch the world. But we're far from this today We are crafting a new interface to AGI. Intelligence that lets you offload your mental workload into a system that begins to think like you and sometimes ahead of you We started Hark with one goal: build the world's most advanced personal intelligence - paired with next-generation hardware designed to serve as a universal interface between humans and machines

Today I'm excited to introduce Hark, a new artificial intelligence lab building the most advanced, personal intelligence in the world We've been in stealth for 8 months, assembling one of the greatest AI and hardware teams on the planet I want to explain why I started Hark and what we're focused on I've spent the last 3 years working on the hardest AI challenge imaginable: giving AI a humanoid body. On the digital side, I've been using all the existing LLM chatbots - and I have to say, they feel incredibly dumb to me AGI, in the limit, should feel like a sci-fi movie. It should be able to listen and talk. It should have persistent memory and be highly personalized. It should see and touch the world. But we're far from this today We are crafting a new interface to AGI. Intelligence that lets you offload your mental workload into a system that begins to think like you and sometimes ahead of you We started Hark with one goal: build the world's most advanced personal intelligence - paired with next-generation hardware designed to serve as a universal interface between humans and machines

Brett Adcock

1,414,945 次观看 • 5 个月前

Recent AI breakthroughs challenge the status quo narrative that only closed, mega labs have the ability to push the frontier of superintelligence. Today we announce Nous Psyche built on Solana - a cooperative training network for generative AI. Psyche coordinates heterogeneous hardware to join a run and train open-source models. We retell the myth of Psyche — a mortal’s quest for retribution against divine odds:

Recent AI breakthroughs challenge the status quo narrative that only closed, mega labs have the ability to push the frontier of superintelligence. Today we announce Nous Psyche built on Solana - a cooperative training network for generative AI. Psyche coordinates heterogeneous hardware to join a run and train open-source models. We retell the myth of Psyche — a mortal’s quest for retribution against divine odds:

Nous Research

754,949 次观看 • 1 年前