It's time for generative AI at Transform

Welcome back to VentureBeat Weekly!?

It’s that time of year again: In two weeks, I’ll be in San Francisco for VentureBeat Transform , which this year will be a two-day, in-person extravaganza on July 11-12 at the Marriott Marquis. It will serve as the first significant independent event for enterprise leaders who want to learn how to leverage generative AI and data technology to transform their businesses.?

As someone who works remotely near NYC, I’m psyched to meet — in real life — top experts from leading brands tackling this journey as well as leading experts sharing how enterprises can turn generative AI into real value. I’ll be moderating several panels and fireside chats, and I’m looking forward to sitting in on sessions featuring companies like Hyatt, Citi, Google, Microsoft, Cohere, Capital One, McDonald’s, United Healthcare, Wayfair, Roblox, AWS and many more.?

I’m also grateful to once again have the opportunity to connect with hundreds of inspiring women leaders attending Transform. The fact that I am a female reporter covering AI is always on my mind, so it’s always particularly powerful to moderate the annual Women in AI Breakfast panel as one of the first Transform events.

This time I’m thrilled to chat with JoAnn Stonier, chief data officer at Mastercard; Emily Roberts, SVP and head of enterprise consumer product at Capital One, and Xiaodi Xhang, VP, seller experience at eBay.?We'll be talking about ensuring diversity in a rapidly-changing AI landscape — how women in AI and data are continuing to actively participate and create positive impact.

I hope you can join me at Transform! As a loyal newsletter reader (thanks!) we would like to offer you our best rate on VB Transform: Please enter VIP Code: VBTSVIP99 during registration to receive the discount.

— Sharon Goldman , senior writer, VentureBeat

Now, onto some of our top-trending AI stories of the past week:

Databricks and MosaicML CEOs say $1.3 billion deal is about helping enterprises create AI IP

The news that Databricks had signed a definitive agreement to acquire AI startup?MosaicML?for an estimated $1.3 billion made headlines yesterday. But for the two companies’ CEOs, the deal was a natural fit, and all about helping speed up enterprise adoption of?generative AI.?

Cohere CEO and president discuss Nvidia and Oracle funding, Hinton comments and the future of LLMs

Back in February, I chatted with Cohere co-founder and CEO Aidan Gomez about the fact that the Toronto-based company, which competes with OpenAI in the LLM space, was “crazy under the radar .”?

It didn’t take long for that to change: Three weeks ago, Cohere, which founded in 2019 by Gomez, Ivan Zhang and Nick Frosst,?announced ?it has raised a fresh $270 million with participation from Nvidia, Oracle, Salesforce Ventures and others — valuing the company at over $2 billion. It felt like good timing to circle back with Gomez as well as Cohere’s president, Martin Kon, to talk about the new funding. But the conversation turned out to be wide-ranging, from the company’s cloud-agnostic stance and Gomez’s take on Geoffrey Hinton’s recent comments on AI risk to the future of LLMs and synthetic data.

Snowflake, Nvidia partner to enable generative AI app development in the Snowflake Data Cloud

Snowflake?and?Nvidia?have partnered to provide businesses a platform to create customized generative artificial intelligence (AI) applications within the Snowflake Data Cloud using a business’s proprietary data. The announcement came today at the?Snowflake Summit 2023.

Integrating Nvidia’s NeMo platform for large language models (LLMs) and its GPU-accelerated computing with Snowflake’s capabilities will enable enterprises to harness their data in Snowflake accounts to develop LLMs for advanced?generative AI?services such as chatbots, search and summarization.

MLPerf 3.0 benchmark adds LLMs and shows dramatic rise in AI training performance

As the hype and momentum behind generative AI continue to grow, so too does the performance of the underlying systems that enable machine learning (ML) training.

MLCommons?today announced the latest set of results for its MLPerf training 3.0 benchmark. This aims to provide an industry standard set of measurements for ML model training performance. MLCommons is an open engineering consortium focused on ML benchmarks, datasets and best practices to accelerate the development of AI. The group has a series of benchmarks for ML including?MLPerf inference, which was last updated in April. Its?MLPerf Training 2.1?results were released in November 2022.