Infrastructure

The AI + a16z podcast captures our thinking on artificial intelligence across a broad swath of areas, from infrastructure to business implications.

Naveen Rao of Databricks joins a16z's Matt Bornstein and Derrick Harris to discuss where we're at in terms of large language model (LLM) adoption.

This episode of the AI + a16z podcast features a panel discussion from back in February, focused on the state — and future — of open source AI models.

The release of the latest Ideogram.ai model is a massive step forward for image models. We're excited to lead their Series A.

Tigris has built a globally available S3-compatible distributed object-storage service that makes the application developer’s job as simple as possible.

Upstash powers caching and messaging for tens of thousands of production applications across four different products, including many AI applications.

Distributional is building a platform for robust and repeatable testing of AI and machine learning models so teams can push to prod confidently.

Mistral is at the center of the open source AI developer community. This is the most promising path to achieve robust and trusted AI systems.

When you hear stories about Amazon's famous "invention machine", we often hear about things like: Memos, six pages exactly and no powerpoints at al! Or, the idea of "work backwards from the press release". But what's lost is the how, as well as the broader narrative of how all companies and leaders, not just Amazon and Bezos, can define their ways as they scale. After all, Amazon was once a small startup, too. So in this episode -- the very first podcast for the new book Working Backwards: Insights, Stories, and Secrets from Inside Amazon -- the authors share firsthand observations and experiences from being in "the room" where it happens, from AWS, Kindle, and Prime to more importantly, the leadership principles, decision making practices, and operational processes that got Amazon there. Can other startups do the same?

We're back to covering multiple items on our show 16 Minutes -- which covers the news, occasional explainers, and teases apart what's hype/ what's real -- as well as where we are on the long arc of innovation.

As companies evolve -- especially from product to sales to scaling operations -- so must the leaders. But can the same person transition across all these phases? When and when not; what are the qualities, criteria, and tradeoffs to be made? Two enterprise startup CTOs share a glimpse into their journeys on the question of to CEO or not to CEO; managing their psychology and tactics for managing transitions; and much more.

Lakes v. warehouses, analytics v. AI/ML, SQL v. everything else... As the technical capabilities of data lakes and data warehouses converge, are the separate tools and teams that run AI/ML and analytics converging as well?

To help data teams stay on top of the changes happening in the industry, this article reviews an updated set of data infrastructure architectures.

0/ Is there an Enterprise Margin Crisis? It's not uncommon to see software startups with surprisingly low margins (30-40%). I believe there is a broader trend going on here, which I explore in this thread.

a16z's newsletter for all things enterprise and B2B -- From AI to open source to software-as-a-service, enterprise software to company building, we share what we’re seeing, hearing, and talking about in our own hallways.

There’s all sorts of interesting tech trends happening right now, including AI, VR/AR, self-driving cars and drones (as well as interesting stuff happening in verticals like healthcare and finance) — and there’s a lot also happening in seemingly more “mature” tech revolutions, such as mobile and cloud. But where are we now, really, with these shifts… and how does that inform how we think about the next couple decades?

APIs (application programming interfaces), observe the guests in this episode of the a16z Podcast, can be described as everything from Lego building blocks to Tetris to front doors to even veins in the human body. Becaus...

What happens when monolithic architectures are broken down into containers and microservices (or when things are broken down into smaller units, not just in infrastructure but perhaps even in company structure too)? From...

We've already talked quite a bit about the Algorithms, Machines, and People lab at U.C. Berkeley (AMPLab) -- all about making sense of big data -- so what happens when the entire world moves towards artificial intelligen...

A funny thing happened on the way to quantum computing: Unlike other major shifts in classic computing before it, it begins -- not ends -- with The Cloud. That's because quantum computers today are more like "physics exp...

Watters, who is the SVP of Product at Pivotal (part of VMWare and therefore also Dell-EMC), is a veteran of monetizing open source — from OpenSolaris (at Sun Microsystems) to Springsource (acquired by VMWare) to Pivotal Cloud Foundry — with plenty of failures, and successes, along the way. He shares those lessons learned in this episode of the a16z Podcast with Sonal Chokshi and general partner Martin Casado (who was co-founder and CTO of Nicira, later part of VMWare before joining Andreessen Horowitz). These lessons matter, especially as open source has become more of a requirement — and how large enterprises bet on big new trends.

As we enter a new era of distributed computing -- and of big data, in the form of machine and deep learning -- storage becomes (even more) important. It might not be sexy, but storage is what makes the internet and cloud...

How will the entire industry be affected as companies not only adopt, but essentially offer, microservices or narrow cloud APIs? How do the trends of microservices, containers, devops, cloud, as-a-service/ on-demand, serverless — all moves towards more and more ephemerality — change the future of computing and even work? Cockcroft (who is now a technology fellow at Battery Ventures) joins this episode of the a16z Podcast, in conversation with Frank Chen and Martin Casado (and Sonal Chokshi) to discuss these shifts and more.

Now that we know to price and plan early, price high -- especially for category-creating or "pre-chasm" businesses -- how do we handle freemium models?

This episode of the a16z Podcast covers all things distributed systems — encompassing cloud and SaaS; A.I., machine learning, deep learning; and quantum computing — to the role of hardware; future interfaces; and data, big and small. Podcast guests Marc Andreessen and Ben Horowitz (in conversation with Scott Kupor and Sonal Chokshi) also share the one piece of advice from a management and go-to-market perspective that all founders should know. And finally, why simulations matter… and what do we make of our current reality if we are all really living in a simulation as Elon Musk believes?

The world's most valuable company, Apple, made a number of seemingly incremental announcements at its most recent annual developer's conference (WWDC) -- that Apple Pay is coming to the web; that Siri is being opened up...

"We really want Apple here... Would you please call Tim Cook?"

It almost seems like gospel -- or at least a given -- today for startups to embrace the cloud. Services like AWS have powered an entire generation of startups that can now spin up new applications, new businesses, and ne...

Developers are more than just influencers inside the enterprise -- they're now buyers, too. That's a huge shift from before, when only IT and other departments had that kind of purchasing power. (It's not just a Silicon...

Infrastructure. It powers everything from cities to computing, yet is sometimes considered "boring" because it is so invisible to so many of us. But as software continues to eat the world, infrastructure has come to the...

In this, world of massive cloud-based applications and services, rolling out software has moved from an episodic event to an almost continuous release cycle. In that environment, software products aren’t as “done” as the...

Every organization these days is clear about the need to get its data act together. But that doesn’t mean the path toward data bliss is clear. Data has gravity. It resides in different places at different organizations -...

The old constraint when it came to technology was hardware -- how many CPUs can I get my hands on. Today, spinning up compute can be done from any smartphone with an AWS account or something similar. The current constrai...

It’s not just the likes of Google, Facebook, and Amazon that lean on a massive and growing corpus of data, today every company is a data-driven company. In this world, access to data -- and how you manage it -- is what m...

There is a shift in enterprise hardware from expensive, proprietary hardware to cheap components plucked directly from the consumer hardware supply chain. While that trend has been underway for some time thanks to compan...

The datacenter has long been -- there's no nice way to put this -- a bit of a snoozer. Expensive boxes running expensive software. No more, says a16z General Partner Peter Levine, who lays out a vision for the datacenter...

a16z Board Partner Steven Sinofsky and Box CEO and co-founder Aaron Levie discuss findings from a study of the information economy that has been built on cloud and mobile. The findings were based on workflow data collect...

There is a perfect storm of three distinct disruptive forces that has the potential to topple nearly every major enterprise software incumbent. And the traditional approach of dealing with technology shifts – through acq...