AI & RoboticsNews

Nvidia became a $1 trillion company thanks to AI. Look inside their lavish Star Trek-inspired HQ  | The AI Beat

Over a million square feet across two massive steel and glass structures. Hundreds of conference rooms named after Star Trek places, alien races and starships, as well as astronomical objects — planets, constellations and galaxies. Acres of greenery and elevated “birds’ nests” where people can work and meet. A bar called “Shannon’s” with a panoramic view and plenty of table space for…
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AI & RoboticsNews

SAP invests directly in three AI startups: Cohere, Anthropic and Aleph Alpha

German enterprise software giant SAP is putting skin into the AI game. The company today announced it has directly invested in three AI startups: Cohere, Anthropic (maker of the Claude 2 LLM service) and Aleph Alpha. While the company did not specify a dollar amount of its investments, a spokesperson told VentureBeat that “they are a signal of SAP’s commitment to offering valuable generative…
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AI & RoboticsNews

Marketing software Anyword adds integrations to ChatGPT, Notion AI, and Canva AI

Anyword, a marketing copywriting software startup now headquartered in New York City, was founded 10 years ago in Israel under a different name: Keywee. The companyh was early with some of the technology trends and buzzwords now gripping Silicon Valley, like natural language processing (NLP) and AI, both of which it has deployed for years, training its GPT 3-based copywriting AI model on two…
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AI & RoboticsNews

Futureverse raises $54M to marry AI and the metaverse

Futureverse, an AI and metaverse technology and content company, has raised $54 million in a new round of funding in an effort to marry AI and the metaverse. 10T Holdings led the round and included participation from Ripple. Futureverse‘s technology platform includes a…
AI & RoboticsNews

How iGenius’s GPT for numbers is evolving language models to give enterprise data a voice

Uljan Sharka, founder and CEO of iGenius, has spent the last seven years working on language models and generative AI. To this point, it’s been all about the technology, from the size of the model to how much training data it uses to inference times. And what he’s learned over the past seven years, and three different development cycles, is that it’s not about the technology – it’s about…
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