🤖 OpenAI CEO Sam Altman’s Q&A at Stanford University

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In today’s AI Report:

• 🌲OpenAI CEO Sam Altman’s Q&A at Stanford University

• 🌻Microsoft’s $10 Billion Energy Deal

• 👨‍🏫LLMs + Grade School Arithmetic = “Overfitting?”

• 🛠5 Trending Tools

• 💰Venture Capital Updates

• 💼Who’s Hiring?

Read Time: 3 minutes

🗞RECENT NEWS

SAM ALTMAN

🌲OpenAI CEO Sam Altman’s Q&A at Stanford University

OpenAI CEO Sam Altman participated in a Q&A at Stanford University, addressing Artificial General Intelligence (AGI), GPT-5, and computing power constraints.

Key Details:

• The core of OpenAI’s research is built around achieving AGI, which OpenAI defines as “a highly autonomous system that outperforms humans at most economically valuable work.”

• “ChatGPT is mildly embarrassing at best,” Altman said. “GPT-4 is the dumbest AI model any of you will ever have to use again, by a lot. But, it’s important to ship early and often, and we believe in iterative deployment.”

• Altman believes in preparing society for AI advancements through responsible and iterative deployment: “Let society co-evolve with the technology. Let society tell us what it collectively wants from the technology.”

• When asked about OpenAI’s for-profit subsidiary, Altman explained: “I think making money is a good thing. I think capitalism is a good thing.” He added that whether the startup burns $500 million, $5 billion, or $50 billion a year, “I genuinely don’t care as long as we create way more value for society.”

• Altman also discussed the importance of global access to computing power, stating that the startup’s mission is to make ChatGPT accessible for “as many people that want to use it.”

Why It’s Important:

• This Q&A at Stanford University provided a glimpse into OpenAI’s roadmap and Altman’s approach toward AI developments. He believes that although AI developments can be shocking initially, society adapts quickly.

• He expressed that OpenAI’s GPT-4 was met with “two weeks of freaking out” followed by a few months of “this thing is crazy and the world has changed forever.” However, “now people are like, ‘Oh, it’s horrible. Where’s GPT-5?”

🚨Watch Altman’s full Q&A at Stanford University here.

🩺 PULSE CHECK

MICROSOFT

🌻Microsoft’s $10 Billion Energy Deal

Microsoft signed a five-year agreement with Brookfield Asset Management (BAM) to develop over 10.5 gigawatts of new renewable energy capacity to support the technology giant’s AI operations.

Key Details:

• The five-year agreement with BAM was estimated to cost between $11.5 billion and $17 billion.

• This partnership enables Microsoft to access a direct pipeline of new renewable energy capacity to support the company’s growing demand for cloud services.

• Microsoft seeks to fuel the surging power demand required to run AI data centers while still meeting the company’s goal of 100% carbon-free energy by 2030.

• Adrian Anderson, General Manager of Renewables, Carbon-Free Energy, and Carbon Dioxide Removal (CDR), explained: “Microsoft wants to use our influence and purchasing power to create a lasting positive impact for all electricity consumers.”

Why It’s Important:

• AI models consume massive amounts of energy to train and operate, relying on data centers that house powerful computers constantly crunching data.

• As Big Tech companies continue to scale and train complex AI models, these companies will enact transformative investments in renewable energy infrastructure across the globe.

AI RESEARCH

👨‍🏫LLMs + Grade School Arithmetic = “Overfitting?”

A research study from Scale AI uncovered significant “overfitting” on popular Large Language Models (LLMs), reinforcing the growing concern of dataset contamination.

“Overfitting” refers to LLMs memorizing specific problems from benchmarks instead of learning general problem-solving skills to apply concepts and perform well on unseen data.

Scale AI developed a new dataset called Grade School Math 1000 (GSM1k), designed to mirror the style and complexity of the GSM8k: the gold standard for measuring elementary mathematical reasoning in AI models.

Popular AI models, including Mistral AI’s Mistral and Microsoft’s Phi-3, experienced accuracy drops of up to 13%. On the other hand, OpenAI’s GPT-4, Anthropic’s Claude 3, and Meta’s Llama 3 all showcased similar performances.

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🔮Browse our always Up-To-Date AI Tools Database.

💰VENTURE CAPITAL UPDATES

• AiDash raises a $58.5M Series C to enhance climate resilience in infrastructure with AI systems.

• CoreWeave secures a $1.1B Series C to expand its GPU cloud infrastructure network.

• Ceartas raises $4.5M to detect AI-generated content.

💼WHO’S HIRING?

• Western Digital (Irvine, CA): Software Development Engineer Firmware Intern, Summer 2024

• Intel (San Jose, CA): Data Analyst Software Engineer Intern, Summer 2024

• Reddit (San Francisco, CA): Data Science Intern, Threat Analytics, Summer 2024

• Relativity Space (Long Beach, CA): Data Science & Computational Mechanics Intern, Fall 2024

• WeRide (San Jose, CA): Software Engineer, Planning & Control, New Grad

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📒FINAL NOTE

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