by Kyle Wiggers@kyle_l_wiggers -- TechCrunch Has OpenAI invented an AI technology with the potential to “threaten humanity”? From some of the recent headlines, you might be inclined to think so. Reuters and The Information first reported last week that several OpenAI staff members had, in a letter to the AI startup’s board of directors, flagged the “prowess” and “potential danger” of an internal research project known as “Q*.” This AI project, according to the reporting, could solve certain math problems — albeit only at grade-school level — but had in the researchers’ opinion a chance of building toward an elusive technical breakthrough. There’s now debate as to whether OpenAI’s board ever received such a letter — The Verge cites a source suggesting that it didn’t. But the framing of Q* aside, Q* in actuality might not be as monumental — or threatening — as it sounds. It might not even be new. AI researchers on X (formerly Twitter), including Meta’s chief AI scientist Yann LeCun, were immediately skeptical that Q* was anything more than an extension of existing work at OpenAI — and other AI research labs besides. In a post on X, Rick Lamers, who writes the Substack newsletter Coding with Intelligence, pointed to an MIT guest lecture OpenAI co-founder John Schulman gave seven years ago during which he described a mathematical function called “Q*.”

Several researchers believe the “Q” in the name “Q*” refers to “Q-learning,” an AI technique that helps a model learn and improve at a particular task by taking — and being rewarded for — specific “correct” actions. Researchers say the asterisk, meanwhile, could be a reference to A*, an algorithm for checking the nodes that make up a graph and exploring the routes between these nodes. Both have been around a while. Google DeepMind applied Q-learning to build an AI algorithm that could play Atari 2600 games at human level… in 2014. A* has its origins in an academic paper published in 1968. And researchers at UC Irvine several years ago explored improving A* with Q-learning — which might be exactly what OpenAI’s now pursuing.

Nathan Lambert, a research scientist at the Allen Institute for AI, told TechCrunch he believes that Q* is connected to approaches in AI “mostly [for] studying high school math problems” — not destroying humanity. “OpenAI even shared work earlier this year improving the mathematical reasoning of language models with a technique called process reward models,” Lambert said, “but what remains to be seen is how better math abilities do anything other than make [OpenAI’s AI-powered chatbot] ChatGPT a better code assistant.”

Here’s a short list of posts for AI founders looking ahead to 2024: Startups must add AI value beyond ChatGPT integration: One criticism …

The world's millionaires are on the move, and their migration patterns are shifting. In 2023, 122,000 high net worth individuals (HNWIs) are expected to move to a new country, with Australia reclaiming the top spot as the most popular destination. The United Arab Emirates, Singapore, the United States, and Switzerland round out the top five countries for HNWI inflows. At the other end of the spectrum, China is expected to lose the most HNWIs in 2023, with 13,500 millionaires leaving the country. India, the United Kingdom, Russia, and Brazil follow closely behind.

Why are millionaires moving? The reasons vary, but economic freedom, tax burdens, and investment opportunities are key factors. Singapore, which boasts the highest level of economic freedom in the world, is a popular destination for HNWIs. Greece, despite its economic challenges, is also expected to see a significant influx of millionaires due to its golden visa program. 

The impact of HNWI migration goes beyond the economic. It also has geopolitical implications, as governments compete to attract and retain the world's economic elite.

by motley fool -- Artificial intelligence (AI) and machine learning (ML) are more than just buzzworthy terms for some cutting-edge companies. They are the foundations on which incredible businesses have been built. Even better, some of these companies make hay in industries essential to the economy. Cybersecurity is top of mind for C-suite executives in all industries, government agencies, school districts, and even nonprofits. Cybercriminals are always on the prowl, costing organizations billions each year. IBM notes that up to 90% of cyberattacks and 70% of breaches come through endpoint devices. AI-powered CrowdStrike Holdings (NASDAQ: CRWD) is the leader in endpoint security with a comprehensive, entirely cloud-based platform. The company's results are on fire, as I'll discuss below. Meanwhile, data centers are crucial for cloud applications, data storage, computing power, and (definitely) complex AI and ML software that require massive computing power. Nvidia (NASDAQ: NVDA) is light-years ahead of its competition, and its data center software and hardware are mission critical. This is why its data center revenue rose 171% year over year last quarter to $10.32 billion.

CrowdStrike is firing on all cylinders

CrowdStrike provides comprehensive security with its Falcon platform. The advantages are several: Falcon is cloud-native (no on-premises hardware required), customizable, and uses AI to analyze data and provide real-time protection. The platform is modular, so customers can choose which modules they want or need. This plays into CrowdStrike's land-and-expand strategy: It gains a customer, proves the platform's worth, and then the customer adds more modules -- creating more revenue. This shows up in the company's dollar-based net retention rate (DBNR), which has been above 120% dating back to the first quarter of fiscal 2019. DBNR measures the year-over-year increase in sales from an average customer. Above 100% is good, and above 120% is excellent. You can probably guess how the chart of annual recurring revenue (ARR) growth looks: The meteoric rise to $2.9 billion in ARR has enabled CrowdStrike to generate $416 million in free cash flow through the second quarter of this 2024 fiscal year and stack up $3.2 billion in cash against $742 million in long-term debt. Having cash on hand to fund growth is crucial in this environment, and the company likely won't have to borrow money at unfavorable interest rates.