Video wird geladen...

Video konnte nicht geladen werden

Beim Laden dieses Videos ist ein Problem aufgetreten. Dies könnte an einem vorübergehenden Netzwerkproblem liegen oder das Video ist möglicherweise nicht verfügbar.

"The most important thing about the intelligence layer is the model.” But what happens when developers can choose from hundreds of them? Vincent Weisser of Prime Intellect joined us for New Defaults to talk open models, model choice, routing, economics, and what happens as intelligence becomes increasingly open and competitive.

OpenRouter

146,385 subscribers

16,312 Aufrufe • vor 4 Tagen •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

12 Kommentare

Profilbild von stochasm

stochasmvor 4 Tagen

@vincentweisser @PrimeIntellect he's got a nice jacket there

Profilbild von OpenRouter

OpenRoutervor 4 Tagen

Watch the full New Defaults episode:

Profilbild von Prime Intellect

Prime Intellectvor 4 Tagen

@vincentweisser Thanks for having us!

Profilbild von Anastasia Crew

Anastasia Crewvor 4 Tagen

@vincentweisser @PrimeIntellect admire your mission and the way you build @vincentweisser. had a lot of fun producing this!

Profilbild von knivesysl

knivesyslvor 4 Tagen

@vincentweisser @PrimeIntellect why does everyone talk like a retard. notice how they start drooling when they use the word “scaling” and “agi”

Profilbild von Viber · fireply.ai

Viber · fireply.aivor 4 Tagen

@vincentweisser @PrimeIntellect more models just means more ways to pick wrong faster honestly

Profilbild von MASA

MASAvor 4 Tagen

@vincentweisser @PrimeIntellect Dynamic switching matters way more than individual weights

Profilbild von Dasha

Dashavor 3 Tagen

@vincentweisser @PrimeIntellect love it!

Profilbild von Ibesh

Ibeshvor 4 Tagen

@vincentweisser @PrimeIntellect model choice only becomes leverage when routing is invisible; otherwise developers inherit a new ops problem where every task starts with a benchmark spreadsheet

Profilbild von Nexqor

Nexqorvor 4 Tagen

@vincentweisser @PrimeIntellect how does routing survive when frontier labs ship their own cheap tiers?

Profilbild von James Camarota

James Camarotavor 4 Tagen

@vincentweisser @PrimeIntellect With hundreds of models, what should a router optimize first for a production agent: quality, latency, cost, or reliability over time?

Profilbild von Tony

Tonyvor 4 Tagen

@vincentweisser @PrimeIntellect With hundreds to choose from, the hard part stops being access and becomes knowing which one to reach for.

Ähnliche Videos

“AI MODELS COULD BECOME 10× SMALLER WITHOUT LOSING MOST OF THEIR INTELLIGENCE.” Mark Zuckerberg says one of the most powerful developments in AI is model distillation: taking the capabilities of a much larger model and transferring them into a much smaller one. - Meta's huge frontier models can serve as "teachers" for smaller models. - Zuckerberg says a model could potentially retain around 90–95% of the larger model's intelligence while being only ~10% of its size. - That means dramatically lower inference costs, memory requirements and computing power. - Developers can distill and customize these capabilities for their own applications. And that's where open-source models come into the picture.

“AI MODELS COULD BECOME 10× SMALLER WITHOUT LOSING MOST OF THEIR INTELLIGENCE.” Mark Zuckerberg says one of the most powerful developments in AI is model distillation: taking the capabilities of a much larger model and transferring them into a much smaller one. - Meta's huge frontier models can serve as "teachers" for smaller models. - Zuckerberg says a model could potentially retain around 90–95% of the larger model's intelligence while being only ~10% of its size. - That means dramatically lower inference costs, memory requirements and computing power. - Developers can distill and customize these capabilities for their own applications. And that's where open-source models come into the picture.

SciTech Era

77,374 Aufrufe • vor 1 Monat

Introducing the OpenRouter MCP, live model intelligence right inside your agent Your agent builds and ships, but when it comes to choosing the right model for the right job, it guesses from 6 month old training data Watch it pick, price, and test the right model:

Introducing the OpenRouter MCP, live model intelligence right inside your agent Your agent builds and ships, but when it comes to choosing the right model for the right job, it guesses from 6 month old training data Watch it pick, price, and test the right model:

OpenRouter

264,764 Aufrufe • vor 2 Monaten

Introducing: Auto Private Model Routing on June Choose Low, Balanced, or High. June picks the right model for every request. Defaults to zero data retention and private models. Powered by Venice. Free to try. Open source. MIT. Try June:

Introducing: Auto Private Model Routing on June Choose Low, Balanced, or High. June picks the right model for every request. Defaults to zero data retention and private models. Powered by Venice. Free to try. Open source. MIT. Try June:

OpenSoftware

112,941 Aufrufe • vor 2 Monaten

Is compute scarcity masking the real economics of AI? interesting point from Peter Fenton: open-weight models are still complex to run well. For now, the big labs have the bundle: model + compute + reliability + access... and thus pricing power. But if compute supply loosens and open model tooling gets easier, routine AI work can more easily move to cheaper/open models.

Is compute scarcity masking the real economics of AI? interesting point from Peter Fenton: open-weight models are still complex to run well. For now, the big labs have the bundle: model + compute + reliability + access... and thus pricing power. But if compute supply loosens and open model tooling gets easier, routine AI work can more easily move to cheaper/open models.

Deirdre Bosa

50,558 Aufrufe • vor 2 Monaten

“50% of DoorDash’s agentic restaurant orders are going to places users have never ordered from before.” Andy Fang tells our CEO Yash Patil what happens when agents become the discovery layer. If models increasingly decide what gets surfaced and bought, companies have a strong reason to train and own that intelligence.

“50% of DoorDash’s agentic restaurant orders are going to places users have never ordered from before.” Andy Fang tells our CEO Yash Patil what happens when agents become the discovery layer. If models increasingly decide what gets surfaced and bought, companies have a strong reason to train and own that intelligence.

Applied Compute

11,128 Aufrufe • vor 18 Tagen

Today is the day! Open Source Surveillance is complete and open for registration! Choose from over 25 modules and take intelligence gathering to a whole new level. #osint #privacy #intelligence #infosec

Today is the day! Open Source Surveillance is complete and open for registration! Choose from over 25 modules and take intelligence gathering to a whole new level. #osint #privacy #intelligence #infosec

Offensive OSINT

191,415 Aufrufe • vor 2 Jahren

The open-source & open-weight frontier is 7 months behind the closed-model frontier. Let’s talk about it. Check out last week’s episode for the reasons why you might want to consider open-source & open-weight models. Welcome to the fourth episode of the Open Model Series with merve, Hugging Face AI/ML engineer & open-sourceress! We have been discussing open-source & open-weight AI: what it is, how it works, and how you can run them on your own compute. Please leave all your questions about open-source & open-weight AI in the comments! This is a super important topic that is novel to most people, and it can be challenging to grasp - so rest assured your questions are shared with many others!

The open-source & open-weight frontier is 7 months behind the closed-model frontier. Let’s talk about it. Check out last week’s episode for the reasons why you might want to consider open-source & open-weight models. Welcome to the fourth episode of the Open Model Series with merve, Hugging Face AI/ML engineer & open-sourceress! We have been discussing open-source & open-weight AI: what it is, how it works, and how you can run them on your own compute. Please leave all your questions about open-source & open-weight AI in the comments! This is a super important topic that is novel to most people, and it can be challenging to grasp - so rest assured your questions are shared with many others!

Harper Carroll

17,279 Aufrufe • vor 20 Tagen

Inferact CEO Simon Mo says open and closed models are converging. The moat is environment: "What really differentiates open-weight models from closed-weight models? In the end, there's not much differentiation. It's more about the distribution strategy and go-to-market strategy. Capability-wise, I don't really see a big gap, not even today." "One of the most important parts is just the data. It's about who gets what data, and then what are the environments you are building to let the model improve on itself." "For Moonshot, they have built some of the best environments for front-end coding... the ability for this model to code and then see what the rendered code is, and then continue looping in this iterative process." "Now, this is about their environment to improve the model. It's not about just source data. It's not about where they get the data from. Rather, it's who can build the best environment and who can make the most optimization and algorithmic choices to leverage all this learning from this environment." "The next year is all gonna be about that: how open-weight model labs are differentiating and really getting the model to meet the real world." Simon Mo

Inferact CEO Simon Mo says open and closed models are converging. The moat is environment: "What really differentiates open-weight models from closed-weight models? In the end, there's not much differentiation. It's more about the distribution strategy and go-to-market strategy. Capability-wise, I don't really see a big gap, not even today." "One of the most important parts is just the data. It's about who gets what data, and then what are the environments you are building to let the model improve on itself." "For Moonshot, they have built some of the best environments for front-end coding... the ability for this model to code and then see what the rendered code is, and then continue looping in this iterative process." "Now, this is about their environment to improve the model. It's not about just source data. It's not about where they get the data from. Rather, it's who can build the best environment and who can make the most optimization and algorithmic choices to leverage all this learning from this environment." "The next year is all gonna be about that: how open-weight model labs are differentiating and really getting the model to meet the real world." Simon Mo

a16z

39,424 Aufrufe • vor 1 Monat

$Sam Altman asks: why are scaling laws a property of the universe? Daniel Selsam says intelligence emerges from compression—and the universe’s knowledge is a fractal you can keep mining. In other words, scaling laws keep working because important concepts are sparse but inexhaustible—and intelligence is what happens when you compress the deep, rare patterns hiding in vast oceans of noise.$

Sam Altman asks: why are scaling laws a property of the universe? Daniel Selsam says intelligence emerges from compression—and the universe’s knowledge is a fractal you can keep mining. In other words, scaling laws keep working because important concepts are sparse but inexhaustible—and intelligence is what happens when you compress the deep, rare patterns hiding in vast oceans of noise.

vitrupo

310,067 Aufrufe • vor 1 Jahr

Jensen Huang was asked whether AI's future is open source or proprietary the question the whole industry keeps fighting over. He didn't pick a side. He said something that quietly ends the fight. "models is a technology, not a product. Model is a technology, not a service" "For the vast majority of consumers, the horizontal layer, the general intelligence, I would really, really love not to go fine-tune my own" "all these industries, their domain expertise, their specialization has to be channeled, has to be captured in a way that they can control, and that it can only come from open models" "the open model industry we're contributing tremendously to it is near the frontier" Everyone else is arguing about which lab wins OpenAI or Anthropic, who has the smartest frontier model this quarter. Jensen is standing on stage saying that's the sideshow. The proprietary model is the convenience layer you rent when you don't care. The open model is the thing you own when the work is yours. Two different products for two different needs not two horses in one race. open models are the second-biggest in the room. Ahead of Anthropic. Behind only OpenAI.

Jensen Huang was asked whether AI's future is open source or proprietary the question the whole industry keeps fighting over. He didn't pick a side. He said something that quietly ends the fight. "models is a technology, not a product. Model is a technology, not a service" "For the vast majority of consumers, the horizontal layer, the general intelligence, I would really, really love not to go fine-tune my own" "all these industries, their domain expertise, their specialization has to be channeled, has to be captured in a way that they can control, and that it can only come from open models" "the open model industry we're contributing tremendously to it is near the frontier" Everyone else is arguing about which lab wins OpenAI or Anthropic, who has the smartest frontier model this quarter. Jensen is standing on stage saying that's the sideshow. The proprietary model is the convenience layer you rent when you don't care. The open model is the thing you own when the work is yours. Two different products for two different needs not two horses in one race. open models are the second-biggest in the room. Ahead of Anthropic. Behind only OpenAI.

Vikram M

12,078 Aufrufe • vor 2 Monaten

When Mudith Jayasekara and I met Gabe Pereyra, we were expecting just another vanilla intro call and instead had the best yarn about research, the state of LLMs, and where intelligence is actually heading. It's rare to meet a founder this deep in the weeds who's also building for one of the most important verticals in this new age of intelligence So it was awesome to sit down with Gabe for an extended discussion on what it take to build agents that can reliably complete work over hours, days, or even longer? We talked about why agents today struggle with search and long context windows and how techniques like KV-cache compaction, synthetic data, and continual learning could help. 0:00 Introduction 0:36 Getting legal agents to review the whole data room 2:08 Data rooms larger than any context window 5:28 How far open-source models can go 7:58 Where specialist models fit in legal AI 10:59 Training legal models when client data is off-limits 13:06 Teaching a model how a law firm works 13:59 What belongs in context vs. model weights 15:36 From firm-wide AI to a model for every lawyer 18:37 What training adds beyond retrieving the right cases 20:26 Why context windows have plateaued 24:01 How models could learn continuously on the job 26:12 Can AI recursively improve AI research? 27:07 Research agents can run experiments but not choose them 30:00 Why open-ended research is hard to train 33:47 Why deployment, not intelligence, is the bottleneck 35:08 The cost of frontier intelligence 36:59 Different neolabs, different paths to intelligence 39:26 Using open datasets to compare research methods 41:13 Conclusion

When Mudith Jayasekara and I met Gabe Pereyra, we were expecting just another vanilla intro call and instead had the best yarn about research, the state of LLMs, and where intelligence is actually heading. It's rare to meet a founder this deep in the weeds who's also building for one of the most important verticals in this new age of intelligence So it was awesome to sit down with Gabe for an extended discussion on what it take to build agents that can reliably complete work over hours, days, or even longer? We talked about why agents today struggle with search and long context windows and how techniques like KV-cache compaction, synthetic data, and continual learning could help. 0:00 Introduction 0:36 Getting legal agents to review the whole data room 2:08 Data rooms larger than any context window 5:28 How far open-source models can go 7:58 Where specialist models fit in legal AI 10:59 Training legal models when client data is off-limits 13:06 Teaching a model how a law firm works 13:59 What belongs in context vs. model weights 15:36 From firm-wide AI to a model for every lawyer 18:37 What training adds beyond retrieving the right cases 20:26 Why context windows have plateaued 24:01 How models could learn continuously on the job 26:12 Can AI recursively improve AI research? 27:07 Research agents can run experiments but not choose them 30:00 Why open-ended research is hard to train 33:47 Why deployment, not intelligence, is the bottleneck 35:08 The cost of frontier intelligence 36:59 Different neolabs, different paths to intelligence 39:26 Using open datasets to compare research methods 41:13 Conclusion

Charlie O'Neill

92,869 Aufrufe • vor 2 Monaten

NeurochainAI is the all-in-one platform for developers to build AI dApps including GPU DePIN, Data Layer, and AI model layer. But what does it actually mean? AI is a $1.8 trillion industry, and NeurochainAI is tapping into 1% of that - as an infrastructure of interconnected GPUs, AI models, and data. Even simpler? Think of us as Ethereum for AI🧠🌐

NeurochainAI is the all-in-one platform for developers to build AI dApps including GPU DePIN, Data Layer, and AI model layer. But what does it actually mean? AI is a $1.8 trillion industry, and NeurochainAI is tapping into 1% of that - as an infrastructure of interconnected GPUs, AI models, and data. Even simpler? Think of us as Ethereum for AI🧠🌐

Neurochain.AI

106,047 Aufrufe • vor 2 Jahren

Everyone’s talking about what Jensen said at GTC about AI capex. But the most important thing he said got almost no attention — that software companies are about to become the biggest resellers of AI tokens in the world. Think about what that means. Workday buys raw intelligence from OpenAI. Wraps it in HR domain expertise. Sells it back as an AI product at a massive markup. That’s not a software company anymore. That’s a refinery. And right now nobody is tracking the economics of that refining layer — what the crude costs, what the refined product sells for, and who’s capturing the spread. This is the most important data gap in AI right now. More on this soon. $NVDA

Everyone’s talking about what Jensen said at GTC about AI capex. But the most important thing he said got almost no attention — that software companies are about to become the biggest resellers of AI tokens in the world. Think about what that means. Workday buys raw intelligence from OpenAI. Wraps it in HR domain expertise. Sells it back as an AI product at a massive markup. That’s not a software company anymore. That’s a refinery. And right now nobody is tracking the economics of that refining layer — what the crude costs, what the refined product sells for, and who’s capturing the spread. This is the most important data gap in AI right now. More on this soon. $NVDA

Nick Dorsey

40,200 Aufrufe • vor 6 Monaten

Frontier models are expensive, slow, and the default choice for most builders. We ran SERV Reasoning against three of them simultaneously. Watch what happens. (The gap is bigger than you think)

Frontier models are expensive, slow, and the default choice for most builders. We ran SERV Reasoning against three of them simultaneously. Watch what happens. (The gap is bigger than you think)

OpenServ

38,123 Aufrufe • vor 5 Monaten

🦙 ollama is used by 9 million developers and 85% of the Fortune 500, giving co-founder and CEO Jeffrey Morgan (Jeffrey Morgan) a unique view into which AI models people are actually using and how that’s changing. Right now, the biggest shift he sees is toward open models, driven by coding agents, falling costs, and capabilities that are rapidly catching up to the frontier labs. On Ollama Cloud, that shift has driven a 150x increase in token usage since the start of the year. In this episode of Lightcone Podcast, Jeff joins Garry Tan, Jared Friedman, Diana, and Harj Taggar to talk about the future of open models and the story behind Ollama, from two years of searching for the right idea to building one of the most widely used AI developer tools in the world. 00:43 — The Shift to Open Models 03:03 — How AI Agents Are Driving Token Usage 05:31 — Are Open Models Catching Up? 08:26 — What Happens When a New Model Launches 11:31 — Ollama as an Operating System for AI 14:05 — The New Opportunities Above the Model Layer 18:19 — Why 80–90% of Enterprise Tokens Could Be Open 20:57 — The Future Is Local and Cloud 26:40 — Why AI Is Coming Back to Your Computer 28:56 — The Coming Era of Unlimited Tokens 32:30 — Do We Still Need a “God Model”? 33:41 — Open Models and Geopolitics 36:14 — The Origins of Ollama 40:36 — Two Years Lost in the Wilderness 42:39 — The Pivot That Changed Everything 47:02 — How Ollama Found a Business Model 49:43 — Why Second-Time Founders Did YC

🦙 ollama is used by 9 million developers and 85% of the Fortune 500, giving co-founder and CEO Jeffrey Morgan (Jeffrey Morgan) a unique view into which AI models people are actually using and how that’s changing. Right now, the biggest shift he sees is toward open models, driven by coding agents, falling costs, and capabilities that are rapidly catching up to the frontier labs. On Ollama Cloud, that shift has driven a 150x increase in token usage since the start of the year. In this episode of Lightcone Podcast, Jeff joins Garry Tan, Jared Friedman, Diana, and Harj Taggar to talk about the future of open models and the story behind Ollama, from two years of searching for the right idea to building one of the most widely used AI developer tools in the world. 00:43 — The Shift to Open Models 03:03 — How AI Agents Are Driving Token Usage 05:31 — Are Open Models Catching Up? 08:26 — What Happens When a New Model Launches 11:31 — Ollama as an Operating System for AI 14:05 — The New Opportunities Above the Model Layer 18:19 — Why 80–90% of Enterprise Tokens Could Be Open 20:57 — The Future Is Local and Cloud 26:40 — Why AI Is Coming Back to Your Computer 28:56 — The Coming Era of Unlimited Tokens 32:30 — Do We Still Need a “God Model”? 33:41 — Open Models and Geopolitics 36:14 — The Origins of Ollama 40:36 — Two Years Lost in the Wilderness 42:39 — The Pivot That Changed Everything 47:02 — How Ollama Found a Business Model 49:43 — Why Second-Time Founders Did YC

Y Combinator

310,621 Aufrufe • vor 17 Tagen

With the rise of artificial intelligence, it is increasingly important to be certain that what we accept as truth is grounded in eternal principles. My invitation for you is to choose truth when deception is easy. Slow down enough to listen to the Spirit and allow Him to direct you.

With the rise of artificial intelligence, it is increasingly important to be certain that what we accept as truth is grounded in eternal principles. My invitation for you is to choose truth when deception is easy. Slow down enough to listen to the Spirit and allow Him to direct you.

Quentin L. Cook

38,862 Aufrufe • vor 4 Monaten

A New Model for Intelligence. The next era of AI won't come from a single system in the cloud, but from a civilization of models owned by the people closest to the problem.

A New Model for Intelligence. The next era of AI won't come from a single system in the cloud, but from a civilization of models owned by the people closest to the problem.

webAI

195,867 Aufrufe • vor 6 Monaten

Reactions to our David French interview included Phoebe Robinson screaming that he's the wrong kind of white person. For adopting a child from Ethiopia, and speaking honestly about what it taught him about racism. This is what happens when politics becomes competitive hatred.

Reactions to our David French interview included Phoebe Robinson screaming that he's the wrong kind of white person. For adopting a child from Ethiopia, and speaking honestly about what it taught him about racism. This is what happens when politics becomes competitive hatred.

The Fifth Column 🖐

22,904 Aufrufe • vor 4 Monaten

This is what happens when you hold the gate open for any and everybody. Disrespectful optics and completely disconnected from the cultural vibes.

This is what happens when you hold the gate open for any and everybody. Disrespectful optics and completely disconnected from the cultural vibes.

The Cake Lady

857,013 Aufrufe • vor 1 Monat