Raghu Raghuram

1/ Today, we announced Gimlet Labs’ $300M Series B, led by @a16z, joined by @SapphireVC as a major investor bringing our valuation to $3B.

We started Gimlet with a simple conviction: inference would become the dominant AI workload, and its infrastructure would need to be rebuilt from the ground up.

$1.1B for the Machine Age.

We’ve raised $300M in Series C funding at a $10.3B valuation from Sequoia, Andreessen Horowitz, Jane Street, Argo, and SK Hynix.

Our mission is to run the world's inference. This round accelerates production of our inference clusters.

We've opened an 80,000-sqft, 10-MW facility 15 minutes from our office to expedite production and prototyping.

本日、ベン・ホロウィッツ・共同創業者兼ゼネラルパートナーをはじめとする、アンドリーセン・ホロウィッツ（a16z）社の皆様にお越しいただき、今年夏に、米国内以外で初となる海外拠点を日本に設けることなどについて、御説明いただきました。

a16z社は、フェイスブック、インスタグラムなど多くのスタートアップを育成、支援した実績を有する世界最大級のベンチャー・キャピタルです。

高市内閣では、『日本成長戦略』の重要な柱として「新技術立国」を掲げ、スタートアップ・エコシステムの構築を目指しています。
また、「経済力」、「技術力」が、我が国の「外交力」、「防衛力」を決するという認識の下、１７の戦略分野の一つとして防衛産業を位置づけています。

そうした中で、米国において、産業分野のイノベーションをリードし、安全保障に貢献するスタートアップを見出し、育成してきたa16z社が、「唯一の海外拠点」を日本に開設し、日本への投資拡大、起業家の育成に乗り出すことは、高市内閣の成長戦略、安全保障戦略を進めていく上で実に心強いことです。

日本のスタートアップ・エコシステムのダイナミズムを取り入れながら、経済の自律性、技術の優位性や不可欠性を確立することで、「安全保障と経済成長の好循環」を実現していきます。

Very few founders have built and scaled a vertically integrated hardware company in the modern era. @RJScaringe is one of them.

At Mind, he’s building the robotics partner @Rivian wanted but couldn’t find.

We believe robotics is just starting to enter its compounding phase. The teams that integrate intelligence, hardware, and deployment into a coherent industrial platform will define the next generation of enduring companies.

Real world deployment is not the final step; it forces clarity in every step, from research to reliability.

Mind is setting out to build that platform. We are incredibly excited to partner with RJ and the entire Mind team.

@DavidGeorge83 @RaghuRaghuram @jamiedsully @espricewright @JacobZietek @appenz

We're excited to invest in Nexthop's $500M Series B.

AI is forcing a complete rebuild of data center infrastructure, and networking is becoming one of the biggest bottlenecks.

@nexthopai is building high-performance Ethernet switches designed natively for AI workloads.

AI training and inference rely on thousands of GPUs communicating constantly. But the networking layer between those GPUs is struggling to keep up:

- AI clusters require thousands of switches routing traffic between GPUs, servers, and storage nodes across multiple network layers
- Each new GPU generation demands dramatically higher bandwidth, lower latency, and greater reliability from the underlying network
- Despite this surge in demand, the data center switching market has been consolidating while engineering complexity continues to rise

Nexthop is taking a different approach.

Instead of adapting legacy networking products built for the cloud, Nexthop designs switches from the ground up for AI traffic patterns, with hardware and software co-designed for hyperscale AI networks.

Their platform combines high-performance hardware with deep support for open-source operating systems and open networking standards, giving hyperscalers the flexibility to extend and integrate the network into their own environments.

Anshul Sadana spent more than 15 years helping build Arista into the defining networking company of the cloud era. He and the Nexthop team are now building the networking company for the AI era.

By @RaghuRaghuram, @shangdaxu, and @appenz

"We are clearly entering a world where a product-minded engineer is now empowered to produce software without writing a line of code for it."

In this conversation, Temporal CEO Samar Abbas joins a16z GPs Sarah Wang and Raghu Raghuram to cover:

- Why agents are going from short-lived and interactive to long-running and async
- Why the engineer of the future manages 15 parallel AI tasks at once
- How OpenAI Codex runs millions of concurrent agent executions on Temporal
- How real-time context engineering is exploding on Temporal
- Why SaaS isn't dead, and value is migrating to APIs

00:00 Introduction
04:03 Temporal's origin story
11:14 Why agents raise the stakes
16:00 Specialized agents need durable RPC
25:20 Deep research agents
30:58 Execution histories as a superpower
39:04 Minimal viable long-running agent architecture
45:07 Context engineering at scale
52:40 Where value accrues: The "five-layer cake" and breakout AI applications

@SamarAtTemporal @sarahdingwang @RaghuRaghuram

As agents increasingly take action in real-world contexts, durable execution is higher stakes than ever. That’s why a16z is thrilled to lead @temporalio’s Series D.

Temporal is the code execution layer for critical workflows. Leading AI labs and AI-native companies, like OpenAI, Replit, Lovable, and Abridge, all rely on Temporal.

Temporal abstracts away that complexity by handling retries, state management, orchestration, recovery, and replay automatically, allowing developers to focus on business logic instead of the difficult plumbing of huge distributed systems.

For long-running agents operating over extended horizons, the durability that Temporal provides is the difference between a compelling demo and a production system.

There are no two people better-suited to solve this problem than Temporal’s cofounders, Samar Abbas and Maxim Fateev, who have spent their careers at the frontier of distributed systems.

We believe Temporal is defining that layer, and we’re thrilled to partner with Samar, Maxim, and the entire team as they build the execution backbone for software that acts.

By @sarahdingwang, @RaghuRaghuram, and @steph_zhang

@SamarAtTemporal @mfateev

We are excited to welcome @RaghuRaghuram as a16z's newest General Partner.

Australia downed India to lift the ICC Men's Cricket World Cup for a record sixth time in Ahmedabad 💪

A flawless performance 👏

#CWC23 | #INDvAUS

This year at #VMwareExplore Las Vegas 2023 the @virtspeaking podcast captured dozens of interviews with @VMware executives, SMEs, customers and partners. On this episode, @vPedroArrow and @Lost_Signal catch up with @VMware CEO @RaghuRaghuram via.vmw.com/explore-raghu

We hope you found a place to explore and thrive this week ☁️ What was your favorite part of #VMwareExplore 2023?blogs.vmware.com/explore/2023/0…

Chandrayaan-3 Mission:
'India🇮🇳,
I reached my destination
and you too!'
: Chandrayaan-3

Chandrayaan-3 has successfully
soft-landed on the moon 🌖!.

Congratulations, India🇮🇳!

#Chandrayaan_3
#Ch3