Former COO at Paypal, David Sacks says that OpenAI recently gave investors a product roadmap update and said their AI models will soon be at PHD level reasoning, act as agents to use tools, meaning the model will be able to pretend to be a human. — - — 👉Get FREE access to the latest AI startup stories! Link in bio. — - — #todayinai #openai #largelanguagemodels
Jensen Huang says that a trillion dollars is being spent on data centers to enable the next, biggest wave of AI to revolutionize business productivity. — - — 👉 Before you go 👋 If you want to keep up with the latest news on AI startups and how they’re changing the world, join 1000+ subscribers reading our newsletter for FREE! Link in bio. — - — #jensenhuang #nvidia #datacenter #datacenters #aidata #artificialintelligence #aitakeover #todayinai
Over the past few months, I was asked multiple times by Staff of the House Committee on Oversight and Accountability whether I am available to testify before the U.S. Congress on Unidentified Anomalous Phenomena (UAPs). As a result, I cleared my calendar for November 13, 2024 and prepared the following written statement. At the end, I was not called to testify before Congress and so I am posting below my intended statement. The Galileo Project under my leadership is about to release this week unprecedented results from commissioning data of its unique Observatory at Harvard University. Half a million objects were monitored on the sky and their appearance was analyzed by state-of-the-art machine learning algorithms. Are any of them UAPs and if so — what are their flight characteristics? Unfortunately, the congressional hearing chairs chose not to hear about these scientific results, nor about the scientific findings from our ocean expedition to the site of the first reported meteor from interstellar space.
Stay tuned for the first extensive paper on the commissioning data from the first Galileo Project Observatory, to be posted publicly in the coming days. Here is my public statement.
Modern imaging systems, such as those used in smartphones, virtual reality (VR), and augmented reality (AR) devices, are constantly evolving to become more compact, efficient, and high-performing. Traditional optical systems rely on bulky glass lenses, which have limitations like chromatic aberrations, low efficiency at multiple wavelengths, and large physical sizes. These drawbacks present challenges when designing smaller, lighter systems that still produce high-quality images.
Readers are unable to reliably differentiate AI-generated from human-written poetry and are more likely to prefer AI poems, according to new research published in Scientific Reports. This tendency to rate AI poetry positively may be due to readers mistaking the complexity of human-written verse for incoherence created by AI and an underestimation of how human-like generative AI can appear.
Fortunately, linguists have developed sophisticated tools using information theory to interpret unknown languages.
Just as archaeologists piece together ancient languages from fragments, we use patterns in AI conversations to understand their linguistic structure. Sometimes we find surprising similarities to human languages, and other times we discover entirely novel ways of communication.
These tools help us peek into the “black box” of AI communication, revealing how AI agents develop their own unique ways of sharing information.
A research team led by Lund University in Sweden has developed an AI tool that traces back the most recent places you have been to.
Microorganisms are organisms, such as bacteria, that are invisible to the naked eye. The word microbiome is used to describe all the microorganisms in a particular environment. Establishing the geographical source of a microbiome sample has been a considerable challenge up to now.
However, in a new study, published in the research journal Genome Biology and Evolution, a research team presents the tool Microbiome Geographic Population Structure (mGPS). It is a unique instrument that uses ground-breaking AI technology to localise samples to specific bodies or water, countries and cities. The researchers discovered that many places have unique bacteria populations, so when you touch a handrail at a train station or bus stop, you pick up bacteria that can then be used to link you back to the exact place.
“In contrast to human DNA, the human microbiome changes constantly when we come into contact with different environments. By tracing where your microorganisms have been recently, we can understand the spread of disease, identify potential sources of infection and localise the emergence of microbial resistance. This tracing also provides forensic keys that can be used in criminal investigations,” says Eran Elhaik, biology researcher at Lund University, who led the new study.
“I can say with certainty that brains work on completely different principles than deep learning, and these differences matter.” writes Jeff Hawkins in a new essay.
Excerpt:
Why should we care about how the brain works?
Brains suggest an alternate way to build AI—one that will replace deep learning as the central technology for creating artificial intelligence.