Lifeboat Foundation

In its quest to develop AI that can understand a range of different dialects, Meta has created an AI model, SeamlessM4T, that can translate and transcribe close to 100 languages across text and speech. Available in open source along with SeamlessAlign, a new translation dataset, Meta claims that SeamlessM4T represents a “significant breakthrough” in the field of AI-powered speech-to-speech and speech-to-text.

“Our single model provides on-demand translations that enable people who speak different languages to communicate more effectively,” Meta writes in a blog post shared with TechCrunch. “SeamlessM4T implicitly recognizes the source languages without the need for a separate language… More.

Professor Ori Bar-Nur and his colleagues at ETH Zurich are pioneering the cultivation of muscle cells in the lab, currently using mouse cells as their primary model. While their current studies are centered on mouse cells, the team is also keen on exploring the potential of human and cow cells. The implications of their research are manifold: lab-cultured human muscle tissue could serve surgical needs, while human muscle stem cells might offer therapeutic solutions for those with muscle diseases. On the other hand, cultivating cow muscle tissue in labs could transform the meat industry by eliminating the necessity of animal slaughter.

For now, however, the ETH team’s research is focused on optimizing the generation of muscle stem cells and making it safer. They have now succeeded in doing so via a new approach.

In what promises to be a revolutionary breakthrough in treatment of various neurological illnesses, Brainstorm is a European project using tiny magnets to restore damaged neurons.

In a new AI research, a team of MIT and Harvard University researchers has introduced a groundbreaking framework called “Follow Anything” (FAn). The system addresses the limitations of current object-following robotic systems and presents an innovative solution for real-time, open-set object tracking and following.

The primary shortcomings of existing robotic object-following systems are a constrained ability to accommodate new objects due to a fixed set of recognized categories and a lack of user-friendliness in specifying target objects. The new FAn system tackles these issues by presenting an open-set approach that can seamlessly detect, segment, track, and follow a wide range of things while adapting to novel objects through text, images, or click queries.

The core features of the proposed FAn system can be summarized as follows:

Artificial Intelligence will gift us with more benefits and advantages than any other invention or discovery in history. On that, everyone agrees.

But it will also require more skills and mastery than anything else. It will place that onus not just on each of us, but also on those in leadership positions who will have to see to their individual transformations and to the transformations of their organizations.

In my previous post (Forbes.com — 8/10/23) I discussed 11 skills necessary for the AI user. In consultation with six respected colleagues, we compiled a sweeping overview of the skill set we’ll all to be effective AI users. No tech involved in that list, just user skills.

Amidst rife competition from the likes of OpenAI, Baidu, and Microsoft, Google looks into the possibility of creating innovative tools using generative AI to create personalized life coaches.

In the ever-intensifying race to dominate the field of artificial intelligence, tech giant Google has been making significant strides to stand at the forefront.

Earlier this year, Google merged its London-based research lab, DeepMind, with its Silicon Valley-based artificial intelligence team, Brain, marking a pivotal move in its endeavor to harness generative AI technology.

A group of esteemed researchers has had a breakthrough by discovering a method to manipulate photons. This groundbreaking experiment demonstrated the collision of electromagnetic waves. Researcher’s…

Angel provides driver and customer support. Naomi teaches high school students. But they are not humans. They’re HumAIns, artificial intelligence (AI) agents.

Designed to handle unscripted communication tasks autonomously and proactively, Angel and Naomi use human-like thought processes to lead conversations instead of merely answering questions. And they get smarter with time and experience.

Continue reading “The AI customer-support agents that can think and act like humans” »

Researchers show it’s possible to make photons that cross paths interact, paving the way for technology breakthroughs.

A research team at the Advanced Science Research Center at the CUNY Graduate Center (CUNY ASRC) has demonstrated that it is possible to manipulate photons so that they can collide, interacting in new ways as they cross paths. Detailed in the journal Nature Physics.

As the name implies, Nature Physics is a peer-reviewed, scientific journal covering physics and is published by Nature Research. It was first published in October 2005 and its monthly coverage includes articles, letters, reviews, research highlights, news and views, commentaries, book reviews, and correspondence.