Lan Jiang

352 posts

Lan Jiang

Lan Jiang

@lanjiang653

@lux_capital

Katılım Kasım 2022
313 Takip Edilen736 Takipçiler
Lan Jiang retweetledi
Lan Jiang retweetledi
Yash Patil
Yash Patil@ypatil125·
Huge congrats to @bernhardsson @akshat_b and the whole @modal team! In an age where so many teams are moving to own their own models, Modal provides powerful primitives we use for training and serving models at scale.
Erik Bernhardsson@bernhardsson

Today we're announcing our Series C funding: $355M at a $4.65B valuation, led by some great investors @generalcatalyst and @Redpoint. We've had insane growth in the last year, but we're still very early. So proud of the team and what we have built so far!

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Modal
Modal@modal·
Frontier models set the floor. Specialized models raise the ceiling. With Modal, @AppliedCompute is training custom agent workforces for companies like DoorDash, Mercor, and Cognition.
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Yash Patil
Yash Patil@ypatil125·
Exactly! The winning strategy is not betting on who has the best model this month. It is building the deployment layer where intelligence actually compounds. That means serving the best possible agent tokens on durable infrastructure: route to any model, train your own when it makes sense, and own the context, harness, environment and interfaces around the agent. Applied Compute is building this customer-first deployment layer. We help customers build intelligent systems where the value compounds on their side.
Chamath Palihapitiya@chamath

If you are running a consulting business and you are deploying Anthropic or OpenAI directly into your organization (I’m looking at you PwC and Accenture) you are letting the fox into the hen house. OpenAI and Anthropic are openly funding and starting competitors to you while also using your usage to drive more success for them. This is not a failure on their part but a failure on your part. Consulting businesses that understand this are adopting a control plane that allows them to arbitrate where tokens go and who generates tokens for them. Controlling the tokens is controlling the spice (Dune). This was a key pillar of 8090’s global partnership with EY and they key feature of our Software Factory. We control token generation and can direct them to any model provider. We are close to another global partnership and will announce it soon. These organizations refuse to accept the disruption standing still or, even worse, by adopting and accelerating the companies who want to disrupt them.

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Yash Patil
Yash Patil@ypatil125·
The real power of forward deployed engineering has always been putting strong technical people directly alongside the operators who own the outcome. That proximity forces the work to solve the actual problem instead of some sanitized version of it. In the AI era this principle has become even more valuable. Agents can now sit inside real workflows and improve from actual decisions, which means the highest-leverage work is extracting the tacit knowledge that lives with subject matter experts, building evaluations that reflect how things actually break, and closing the production feedback loop so agents get better from real outcomes.
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Citrini
Citrini@citrini·
For the better part of 4 years, I’ve considered myself reasonably early to emerging sub-themes in AI and Robotics. Every time I begin researching a new one, I encounter promising private companies and, without fail, @GavinSBaker or @wolfejosh are already investors in them.
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Yash Patil
Yash Patil@ypatil125·
Harvey is a great example of a company carving out a strong competitive position by building proprietary intelligence We had a great experience teaming up with them to support their new Legal Agent Benchmark with post-training and eval methodology Thanks @gabepereyra for visiting during our team all-hands today to break down what proprietary intelligence looks like in law!
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Jacob Teo
Jacob Teo@jacobtpl·
seeing all the old house photos really brings me back. lots of fun memories and late night gym sessions... wish I took more pictures but all I have is us trying to recreate the cognition logo with dumbbells
Jacob Teo tweet mediaJacob Teo tweet media
Colossus@colossusmag

Scott Wu is the co-founder of Cognition AI, one of the fastest-growing companies in history. He’s also the greatest competitive programmer the US has ever produced. You may have seen him doing impossible card tricks and mental math. You’ve never seen him asked about weed, Michael Jordan, cancer, and human consciousness over a punnet of strawberries. That is what Colossus editor-in-chief Jeremy Stern did on a recent visit to San Francisco. For those less familiar with @ScottWu46: In 2nd grade, he entered a math competition for 7th graders, lost, and was so furious he still fumes about it 20 years later. The next year he entered the 9th-grade division as a 3rd-grader and got a perfect score. Then he won first place at the US national middle-school math competition and three straight gold medals at the International Olympiad in Informatics, where he became the greatest American gold-medalist and coach in history. Most of the people running the biggest AI companies met as teenagers, competing for their countries on international math and science teams. OpenAI’s Greg Brockman, Anthropic’s Dario Amodei, Meta’s Alexandr Wang, to name just a few. Most agree that the von Neumann among them was Scott Wu. In November 2023, a few weeks after his mother died of lung cancer, on the day Sam Altman was fired from OpenAI, Wu founded his own AI company: Cognition. He was 26 and saw earlier than almost anyone that AI would converge on agents that work in the background, 24/7, like coworkers. He shipped Cognition’s AI software engineer Devin in March 2024. It worked poorly, and he took intense public criticism for it. Now, in its first 18 months of service, Devin has generated $445 million of revenue run rate and usage has doubled every eight weeks. The US Army, Goldman Sachs, and Mercedes-Benz are all customers. Cognition is raising at a valuation around $25 billion. @JeremySternLA sat down with Wu, the emperor of the nerds, to ask the questions we’d all ask one of the smartest people in America—building the most consequential technology of our generation—if we ever got the chance. As well as MJ and weed, they talk about the cluster of competitive math prodigies behind so much of AI, what makes us human when AGI arrives, and why Wu believes he was put on this earth to teach AI how to code. Read the piece below.

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Linden Li
Linden Li@lindensli·
We started the company knowing that, despite remarkable progress on public frontier models, there was a frontier that had not yet been explored. The destination was clear (finding ways to leverage data, internal processes, and knowledge built up over many decades to produce systems that get better over time), but we didn't have the infrastructure to get there. The "private frontier" belief has played out more now, as the winners of this era will get there by honing their internal intelligence every day.
Yash Patil@ypatil125

x.com/i/article/2054…

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Josh Wolfe
Josh Wolfe@wolfejosh·
Love this. Brian @SchimpfBrian is the BEST!
FORTUNE@FortuneMagazine

Meet @anduriltech CEO Brian Schimpf, the engineer-CEO building America’s $31 billion weapons startup. The Pentagon is turning to Anduril for drones, missiles, and software. It’s the biggest sign yet that Silicon Valley is shaking up the military-industrial complex. bit.ly/48HpFXv

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Yash Patil
Yash Patil@ypatil125·
We are building across the stack at AC! Enterprise agents should work like your employees do - getting better over time by learning from experience! All of this starts with building durable infrastructure for cloud agents. Context Engine is just the start!
Applied Compute@appliedcompute

Introducing the AC Context Engine: enterprise-grade infrastructure to continuously encode nuanced institutional knowledge into a living artifact (Contextbase). We find that our Contextbases can be the unlock to moving the Pareto frontier on cost and intelligence.

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Josh Wolfe
Josh Wolfe@wolfejosh·
What an incredible team and incredible privilege to be partnered with them. @hamutalm + @AlonDror1 + @kela_tech 🇺🇸🇮🇱💪
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Josh Wolfe
Josh Wolfe@wolfejosh·
1/ Absolutely extraordinary must-read from my friend @scmallaby Every book of his from Greenspan (the man who knew) to hedge fund masters (more money than god) to best book on VC (the power law) captured with insane access + clarity the stories nobody else knew NOW...
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Linden Li
Linden Li@lindensli·
It's painful to type in the same instructions every time you begin an agent session (for me, it's often sharing the same context on how our GPU cluster is setup) and to watch an agent spend thousands of tokens to rediscover knowledge it found from previous use. Contextbases are our attempt to "cache" inference compute by capturing institutional knowledge that's already known and making it accessible at runtime. It's a prerequisite to developing systems that continuously improve over time, complementary to methods we've shared previously that update the model's weights.
Applied Compute@appliedcompute

Introducing the AC Context Engine: enterprise-grade infrastructure to continuously encode nuanced institutional knowledge into a living artifact (Contextbase). We find that our Contextbases can be the unlock to moving the Pareto frontier on cost and intelligence.

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Sam Denton
Sam Denton@samueldenton·
Brief obligatory update: I recently joined @appliedcompute to do research on our platform enabling Specific Intelligence for enterprises. Excited to share our first publication on what we've been doing with Contextbases. Looking forward to sharing more soon!
Applied Compute@appliedcompute

Introducing the AC Context Engine: enterprise-grade infrastructure to continuously encode nuanced institutional knowledge into a living artifact (Contextbase). We find that our Contextbases can be the unlock to moving the Pareto frontier on cost and intelligence.

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Rhythm Garg
Rhythm Garg@rhythmrg·
Applied Compute is extremely customer-aligned; we will build the best agent possible for a use case, whether that means training open-source model weights or continuously improving the context supplied to a closed-source model. We are excited to share some of our work on the latter. If you're interested in research engineering across the agent stack, consider joining us!
Applied Compute@appliedcompute

Introducing the AC Context Engine: enterprise-grade infrastructure to continuously encode nuanced institutional knowledge into a living artifact (Contextbase). We find that our Contextbases can be the unlock to moving the Pareto frontier on cost and intelligence.

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Tiffany Zhao
Tiffany Zhao@tiffzhao05·
I left Google DeepMind, moved from SF to NYC, all within 2 weeks to join @quadrillion_ai — to build the future of automated research intelligence with the highest slope founder and most talent dense team. I grew up in Silicon Valley — the old Facebook office was my second home. I’d hang out there after school, drawing with my crayons while looking around at the sea of computers with lines of code. Since a young age, I felt empowered to have an array of interests beyond tech: piano, ballet, figure skating, art. The valley embraced diversity of thought, and that’s what inspired me to stay for Stanford and my career thus far. But today, SF is one big hive-mind. So, I moved to NYC, away from family and friends to build a company that doesn’t need to rely on a bubble to survive. I’m meeting customers day after day in all kinds of verticals, connecting with them in different ways and seeing our product bring real value. Here, I’m able to live in diversity of thought. I’m excited to build the future of research in the city of opportunity. Let’s chat if this excites you.
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