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Fine-tuning large language models (LLM) has become an important tool for businesses seeking to tailor AI capabilities to niche tasks and personalized user experiences. But fine-tuning usually comes with steep computational and financial overhead, keeping its use limited for enterprises with limited resources.

To solve these challenges, researchers have created algorithms and techniques that cut the cost of fine-tuning LLMs and running fine-tuned models. The latest of these techniques is S-LoRA, a collaborative effort between researchers at Stanford University and University of California-Berkeley (UC Berkeley).

Barbara Corcoran almost missed out on “the best hire” she ever made — all because the prospective employee seemed too introverted.

“When I started my business [in 1973], I needed people to join my real estate company,” the millionaire investor and real estate entrepreneur said in a recent TikTok video. “But I had little to offer, and good people were really hard to get.”

In walked Esther Kaplan, who would eventually become Corcoran’s business partner and longtime president of The Corcoran Group. But at the time, Kaplan didn’t seem like the right fit for the sales position she’d applied for, Corcoran said.

As the dawn of generative AI unfolds, a distinct separation will emerge among professionals and businesses: those who leverage this transformative technology to enhance productivity and innovation and those who lag behind.

Discover how adopting a generative AI mindset, blending adaptability, curiosity, and collaboration, is key to thriving in the rapidly evolving professional landscape,.

Nvidia is on a tear.

But “there are no companies that are assured survival,” Huang warned Thursday at the Harvard Business Review’s Future of Business event.

Nvidia in its 30-year history has faced several existential threats, which helps explain why Huang recently told the Acquired podcast that “nobody in their right mind” would start a company. For example, it almost went bankrupt in 1995 after its first chip, the NV1, failed to attract customers. It had to lay off half its employees before the success of its third chip, the RIVA 128, saved it a few years later.

Continue reading “Nvidia CEO Jensen Huang says his AI powerhouse is ‘always in peril’ despite a $1.1 trillion market cap: ‘We don’t have to pretend…we feel it’” »

Kynikos Associates founder and legendary short seller Jim Chanos has highlighted the disparity between the public perception and actual performance of Tesla Inc. TSLA.

What Happened: In an interview with the Institute for New Economic Thinking, Chanos pointed out a common misbelief held by many Tesla admirers. He said the electric vehicle giant is seen as a multi-faceted entity — an AI firm, an alternative energy business, and a robotics organization.

This image, Chanos argues, is a result of Elon Musk’s compelling portrayal of Tesla as a future-focused company.

Elon Musk is getting the Hollywood treatment. Variety reports that indie movie studio A24 has won the rights to adapt Walter Isaacson’s recent biography about the business magnate, with “Black Swan” and “Requiem for a Dream” director Darren Aronofsky slated to direct. There’s no official word on who’s playing Musk yet, though there’s plenty of wild suggestions online.

According to the report, studios were embroiled in “heated competition” for Isaacson’s latest book, which was released this September. The author’s last biography on a tech titan, Steve Jobs, was also adapted into a movie of the same name in 2015. Of course, the main attraction here is Musk, whose penchant for controversy is matched only by his enormous popularity.

Continue reading “A24’s Making an Elon Musk Biopic Directed by Darren Aronofsky” »

Will AI put game developers out of business? Find out why we think so after developing a new udemy course “Fast and Furious Game Dev with JavaScript and AI.”

Machine learning (ML) is now mission critical in every industry. Business leaders are urging their technical teams to accelerate ML adoption across the enterprise to fuel innovation and long-term growth. But there is a disconnect between business leaders’ expectations for wide-scale ML deployment and the reality of what engineers and data scientists can actually build and deliver on time and at scale.

In a Forrester study launched today and commissioned by Capital One, the majority of business leaders expressed excitement at deploying ML across the enterprise, but data scientist team members said they didn’t yet have all the necessary tools to develop ML solutions at scale. Business leaders would love to leverage ML as a plug-and-play opportunity: “just input data into a black box and valuable learnings emerge.” The engineers who wrangle company data to build ML models know it’s far more complex than that. Data may be unstructured or poor quality, and there are compliance, regulatory, and security parameters to meet.

01. AI’s model outperforms Meta’s Llama 2 on certain metricsStartup to offer open-source model; proprietary options laterA Chinese startup founded by computer scientist Kai-Fu Lee has become a unicorn in less than eight months on the strength of a new open-source artificial-intelligence model that outstrips Silicon Valley’s best, on at least certain metrics.

The company, 01.AI, has reached a valuation of more than $1 billion after a funding round that included Alibaba Group Holding Ltd.’s cloud unit, Lee said in an interview. The chief executive officer of venture firm Sinovation Ventures will also be CEO of the new startup. He began assembling the team for 01.AI in March and started… More.

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Continue reading “AI Pioneer Kai-Fu Lee Builds $1 Billion Startup in Eight Months” »