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In January, new reports on Apple’s long-awaited augmented reality/virtual reality headset were released. And if what’s in these reports is even partially true, Apple is poised to give the world one of the most jaw-dropping, powerful pieces of technology in history (again) — which is why it was a bit surprising that this news didn’t make more of a splash.

This is the same company that has fans enter lotteries for tickets to corporate keynote addresses! Yet, outside of the usual tech blogs and a few newspaper columns, the future of Apple’s AR/VR device went largely unnoticed.

Geoffrey Hinton, a VP and engineering fellow at Google and a pioneer of deep learning who developed some of the most important techniques at the heart of modern AI, is leaving the company after 10 years, the New York Times reported today.

According to the Times, Hinton says he has new fears about the technology he helped usher in and wants to speak openly about them, and that a part of him now regrets his life’s work.

AI is having its moment on tech earnings calls for the second consecutive quarter, following the widely popular launch of OpenAI’s ChatGPT in late November. But not every company has the same plans for the new technology.

Nvidia (NVDA) is selling AI powered supercomputers. Microsoft (MSFT) is integrating ChatGPT into its search engine to compete with Google (GOOGL), which has its own AI searchbot.

Meta’s approach is slightly different. The core business for Meta since the early days of Facebook has been advertising sales, which still account for 98% of the company’s quarterly revenue. So naturally, enhancing advertisements with AI is where Meta believes the new technology can be most impactful.

Can we ensure that AI is used ethically? Will AIs themselves develop empathy and ethics? That’s the topic I’d like to discuss today. It’s important.

I recently sat down with Rana el Kaliouby, PhD, AI researcher and Deputy CEO of Smart Eye, at my private CEO Summit Abundance360 to explore these questions. Rana has been focused on this very topic for the past decade.

Continue reading “Can AI Develop Empathy & Ethics?” »

Insulin-mTOR signaling drives anabolic growth in organismal development, while its late-life antagonistic pleiotropy affects aging and compromises lifespan across animal phylogeny. Here we identify LPD-3 as a megaprotein that orchestrates the tempo of insulin-mTOR signaling during C. elegans aging. We find that an agonist insulin INS-7 is drastically over-produced and shortens lifespan in lpd-3 mutants, a C. elegans model of human Alkuraya-Kučinskas syndrome. LPD-3 forms a bridge-like tunnel megaprotein to facilitate phospholipid trafficking to plasma membrane. Lipidomic profiling reveals increased abundance of hexaceramide species in lpd-3 mutants, accompanied by up-regulation of hexaceramide biosynthetic enzymes, including HYL-1 (Homolog of Yeast Longevity). Reducing HYL-1 activity decreases INS-7 levels and rescues the shortened lifespan of lpd-3 mutants through insulin receptor/DAF-2 and mTOR/LET-363. LPD-3 antagonizes SINH-1, a key mTORC2 component, and reduces protein abundance with age in wild type animals. We propose that LPD-3 acts as a megaprotein brake for aging and its age-dependent decline restricts lifespan through the sphingolipid-hexaceramide and insulin-mTOR pathways.

The authors have declared no competing interest.

MIT professor Max Tegmark is stressed about the potential impact of artificial general intelligence (AGI) — and thinks you should be, too.

Alphabet cited artificial intelligence the most often on its investor call last week, followed by Microsoft, Meta, and Amazon.

As one of the OMICS in systems biology, metabolomics defines the metabolome and simultaneously quantifies numerous metabolites that are final or intermediate products and effectors of upstream biological processes. Metabolomics provides accurate information that helps determine the physiological steady state and biochemical changes during the aging process. To date, reference values of metabolites across the adult lifespan, especially among ethnicity groups, are lacking. The “normal” reference values according to age, sex, and race allow the characterization of whether an individual or a group deviates metabolically from normal aging, encompass a fundamental element in any study aimed at understanding mechanisms at the interface between aging and diseases.

While the world has been captivated by recent advances in artificial intelligence, researchers at Johns Hopkins University have identified a new form of intelligence: organoid intelligence. A future where computers are powered by lab-grown brain cells may be closer than we could ever have imagined.

What is an organoid? Organoids are three-dimensional tissue cultures commonly derived from human pluripotent stem cells. What looks like a clump of cells can be engineered to function like a human organ, mirroring its key structural and biological characteristics. Under the right laboratory conditions, genetic instructions from donated stem cells allow organoids to self-organize and grow into any type of organ tissue, including the human brain.

Although this may sound like science-fiction, brain organoids have been used to model and study neurodegenerative diseases for nearly a decade. Emerging studies now reveal that these lab grown brain cells may be capable of learning. In fact, a research team from Melbourne recently reported that they trained 800,000 brain cells to perform the computer game, Pong (see video). As this field of research continues to grow, researchers speculate that this so-called “intelligence in a dish” may be able to outcompete artificial intelligence.