Sequoia Capital
@sequoia • 817,303 subscribers
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In 2014, Keller Cliffton Cliffton shut down his robotic toy startup to build a drone delivery network for life-saving medical supplies. Everyone said it wouldn’t work. Today, Zipline delivers for hospitals around the world. Now it’s reinventing how delivery works with Platform 2 - starting with Walmart and Chipotle in the US. This is a story of betting everything to transform the world. Featuring Keenan Wyrobek, Ryan Oksenhorn, Maggie Jim, Alfred Lin Hosted by Roelof Botha 00:00 – Chewing Glass 00:55 – Discovering Entrepreneurship 02:00 – From Robots to Real Problems 03:00 – The Vision for Global Health Logistics 04:30 – Betting on Rwanda 06:00 – Building the System 08:00 – The First Flight 09:15 – Breakthrough and Scale 11:15 – The Moment of Validation 12:30 – Platform Two: A New Bet 14:15 – Seeing Is Believing 15:45 – The Next Frontier 16:30 – Never Giving Up
Sequoia Capital1,340,956 просмотров • 10 месяцев назад
We’re launching our latest venture and seed funds to back outlier founders at the start of their journey. With AI driving a platform shift as big as the internet, generational companies will be built. We’re seeking the visionaries who will build them.
Sequoia Capital674,942 просмотров • 10 месяцев назад
"Is it Bitter Lesson-pilled?" — the most used, and most misused, phrase in AI right now. Richard Sutton sums it up on the latest Training Data with Khurram Javed , Sonya Huang 🐥, Alfred Lin "Don't be distracted by human knowledge, as AI traditionally has been many times. Instead, focus on learning methods that will scale with computation, like search and like learning."
Sequoia Capital25,531 просмотров • 16 дней назад
“Many of the best things we’ve learned have come through failures.” Ilkka Paananen built Supercell into Europe’s first decacorn by inverting the standard corporate hierarchy and radically accepting failures. Hear the story of Supercell today on a new episode of Crucible Moments.
Sequoia Capital314,594 просмотров • 10 месяцев назад
Today's AI models train once. We don't work that way. We learn continuously, forget what doesn't matter, and retain what does. That gap is what Dan Biderman and Jessy Lin are closing at Engram. AI that never stops learning, with memory that lives inside the model instead of bolted on as an afterthought. In our latest Training Data episode we get into why memory is the next frontier: why the brain forgets on purpose, why RAG is a band-aid, and what becomes possible when a model is always training. 00:00 Introduction 00:59 Always Training Explained 01:51 Beyond Context Windows 03:29 Ngram Product Overview 04:34 Adapters And Training Signals 05:32 Internalize Vs Externalize 06:49 Compute And Token Savings 08:19 Teams First Then Individuals 08:51 Memorization Vs Understanding 12:47 Dreams And Offline Digestion 14:08 Training Beats Curation 15:19 Why Everyone Needs A Model 21:44 Bitter Lesson And Architecture 24:44 RAG Killer And KV Cache 31:38 Future Of Memory And Models
Sequoia Capital83,323 просмотров • 2 месяцев назад
In Iain Banks' The Player of Games, a civilization chooses its emperor by playing a strategy game. That may be the best metaphor for AI right now: multiple players, one board, and everyone at the table believes the winner controls AGI – whatever that turns out to mean. David Cahn joined Alex Kantrowitz on Big Technology to discuss: - How each player is playing the board: Anthropic, OpenAI, XAI, Google, Meta, Microsoft, and the rest - Why the $200B question is now the $1.5T question - Why nothing short of AGI justifies the spend - Whether humans will end up worshiping AI and more.
Sequoia Capital31,378 просмотров • 1 месяц назад
The unwritten rule of AI research: prove your architecture at small scale, then earn the compute to scale it. Jerry Tworek thinks that rule may have quietly killed the transformer's competitors. RL showed almost nothing interesting until it crossed a compute threshold – the capabilities simply don't appear below a baseline. If that's true of RL, it's probably true of other architectures too. Which means there could be entire families of ideas sitting in the discard pile, written off before they were ever given enough compute to show anything at all. That's the bet behind Core Automation: run architecture search at the scale where the answers actually show up.
Sequoia Capital26,746 просмотров • 1 месяц назад
Building the most automated AI lab in the world doesn’t mean removing humans. co-founder Jerry Tworek's version of automated: give each researcher maximum agency. Walking gets you some distance. A bike gets you further. A car, much further. Farming by hand works a small plot; a machine works a vastly larger one. A single researcher can now move through ideas faster than entire teams could a few years ago. The choice every lab faces: retrofit old team structures around that, or build natively for it. They chose to build natively.
Sequoia Capital27,722 просмотров • 1 месяц назад
Last week we hosted our 2nd @Sequoia AI Ascent. We’re sharing some of the day’s most memorable talks. Hear thoughts from @mistralAI’s Arthur Mensch, Paul Jankura’s Daniela Amodei, AI Fund’s Andrew Ng, founding member of OpenAI Andrej Karpathy, and more to come.
Sequoia Capital201,182 просмотров • 2 лет назад
.Markus Villig and team built the top ride hailing company across much of Europe, Africa and the Middle East by trusting the data when everyone thought they were crazy to launch in non-obvious markets. From bootstrapping in Estonia on 5k Euros to a global leader in mobility, hear the story of Bolt on a new Crucible Moments.
Sequoia Capital54,936 просмотров • 9 месяцев назад
Before Palo Alto Networks became a cybersecurity giant, its founder was a teenage hacker in Israel writing some of the world’s earliest computer viruses. That curiosity led Nir Zuk to Unit 8200, to joining the early team of Check Point, and ultimately into a career-defining rivalry that shaped the next 30 years of cybersecurity. In a new episode of Crucible Moments, Nir recounts the wild early days: leaving Check Point to build his own startup, joining competitor NetScreen, driving around with a “CHKPKLR” (Check Point killer) vanity plate, and getting acquired by Juniper only to be told on day one they didn’t want his product. So he left. Others followed. And Palo Alto Networks was born.
Sequoia Capital50,793 просмотров • 9 месяцев назад
12 years ago a top scientist said AI would wipe out radiology. Computer vision spread through every scan – and radiology demand went UP. Hospitals hired more radiologists. NVIDIA’s Jensen Huang on why we keep confusing a job's tasks with its purpose.
Sequoia Capital19,020 просмотров • 2 месяцев назад
Older people use ChatGPT as a Google replacement. People in their 20s and 30s use it as a life advisor. People in college use it as an operating system. Sam Altman discussed AI's generational divide, his vision for OpenAI to become your "core AI subscription" & more at AI Ascent.
Sequoia Capital60,757 просмотров • 1 год назад
Don't mistake task for purpose. NVIDIA's Jensen Huang in conversation with Konstantine Buhler: "Typing is not the job of a software engineer. Coding is not their job. Solving problems is their job." Jensen says AI is creating more jobs, not destroying them. Why? AI lets us solve problems better than ever.
Sequoia Capital14,788 просмотров • 2 месяцев назад