I found this on NewsBreak:#Publichealth #Computerscience #AI
AI holds the potential to help doctors find early markers of disease and policymakers to avoid decisions that lead to war. But a growing body of evidence has revealed deep flaws in how machine learning is used in science, a problem that has swept through dozens of fields and implicated thousands of erroneous papers.
Tiangong is a full-size humanoid robot from China that stands as tall as an average human, can jog and is capable of running on electric power.
Go to https://hensonshaving.com/isaacarthur and enter “isaacarthur” at checkout to get 100 free blades with your purchase. We think very highly of the human brain, after all, it’s what lets us think about anything in the first place, but Nature is vast, and our primate brains are not the end-all and be-all of neural engineering. Join this channel to get access to perks: / @isaacarthursfia Visit our Website: http://www.isaacarthur.net Join Nebula: https://go.nebula.tv/isaacarthur Support us on Patreon:
/ isaacarthur Support us on Subscribestar: https://www.subscribestar.com/isaac-a… Group:
/ 1,583,992,725,237,264 Reddit:
/ isaacarthur Twitter:
/ isaac_a_arthur on Twitter and RT our future content. SFIA Discord Server:
/ discord Credits: Alternative Intelligence: The Other A.I. Episode 448; May 23, 2024 Produced & Narrated by: Isaac Arthur Written by: Erik Eldritch & Isaac Arthur Editor: Darius Said Music Courtesy of Epidemic Sound http://epidemicsound.com/creator Stellardrone, “Red Giant”, “Ultra Deep Field”, “Cosmic Sunrise” Sergey Cheremisinov, “Labyrinth”, “Forgotten Stars” Taras Harkavyi, “Alpha and…” Miguel Johnson, “So Many Stars”
Scientists put their heads together for an insane medical breakthrough.
Neuroscience and biomedical engineering startup BrainBridge announced that it has created an AI-mechanized system for performing head transplants.
The procedure would graft a head onto the body of a brain-dead donor, maintaining the memories, cognitive abilities and consciousness of the transplanted individual.
I found this on NewsBreak: #Design
Leveraging advanced computational techniques in physical sciences has become vital for accelerating scientific discovery. This involves integrating large language models (LLMs) and simulations to enhance hypothesis generation, experimental design, and data analysis. Automating these processes aims to streamline and democratize access to cutting-edge research tools, pushing the boundaries of scientific knowledge and improving efficiency across various scientific domains.
Researchers face a significant challenge in effectively simulating observational feedback and integrating it with theoretical models in physical sciences. Traditional methods often need a universal approach that can be applied across various scientific fields, leading to inefficiencies and limiting the potential for innovative discoveries. The need for a more comprehensive and adaptable framework is evident to address this issue and advance scientific inquiry.
All sensations—hunger, feeling pain, seeing red, falling in love—are the result of physiological states that an LLM simply doesn’t have. Consequently we know that an LLM cannot have subjective experiences of those states. In other words, it cannot be sentient.
An LLM is a mathematical model coded on silicon chips. It is not an embodied being like humans. It does not have a “life” that needs to eat, drink, reproduce, experience emotion, get sick, and eventually die.
It is important to understand the profound difference between how humans generate sequences of words and how an LLM generates those same sequences. When I say “I am hungry,” I am reporting on my sensed physiological states. When an LLM generates the sequence “I am hungry,” it is simply generating the most probable completion of the sequence of words in its current prompt. It is doing exactly the same thing as when, with a different prompt, it generates “I am not hungry,” or with yet another prompt, “The moon is made of green cheese.” None of these are reports of its (nonexistent) physiological states. They are simply probabilistic completions.
AI has already started replacing voice agents’ jobs. Now, companies are exploring ways to replace the existing computer-generated voice models with synthetic versions of human voices. Truecaller, the widely known caller ID service, is the latest to take this approach with its announcement that it will now allow customers to use its AI-powered Assistant to answer phone calls in their own voice.
The new experience comes via a partnership with Microsoft that allows the Swedish company to use the Redmond giant’s Personal Voice technology, introduced in November as part of Azure AI Speech.
By using Microsoft’s Personal Voice, Truecaller’s Assistant, available to paid users, will be able to replicate users’ voices in order to greet and respond to callers. This is in addition to the preset system-generated voice options available to users through the digital assistance feature that helps answer phone calls for you, screen unknown calls, take messages, respond on your behalf or even record the call.
More funding is being poured into startups focused on AI. DeepL, which builds automated text translation and writing tools that compete against the likes of Google Translate and Grammarly, said on Wednesday that it has raised an additional $300 million. It is now valued at $2 billion, post-money.
This round, led by Index Ventures, underscores the frenetic interest that investors have in AI startups at the moment and how companies are capitalizing on that opportunity while they can. DeepL, which is still not profitable, was valued at $1 billion in January 2023, when it raised just over $100 million.
The new money will be used to drive more sales and marketing, as well as further research and development.
NVIDIA’s Blackwell GB200 AI servers are anticipated to see major traction, reaching 2 million units shipped in 2025 & utilizing new packaging tech.
NVIDIA To Overcome CoWoS Supply Chain Bottlenecks By Shifting To The Newer “PFLO” Standard, 420K Units Shipping This Year With Up To 2 Million Anticipated For 2025
The success of NVIDIA’s Hopper AI products last year not only uplifted the company’s economics to new heights but also revealed massive flaws in the supply chain. Due to these flaws, the products became victims of long order backlogs. The main culprits at that time were HBM & CoWoS supply, which was in a much inferior position to what it is today. Despite seeing massive upgrades, NVIDIA has decided to resolve CoWoS issues with its latest Blackwell product, as the firm is rumored to have switched to a newer packaging technology by 2025–2026.
So dl what you can…
WASHINGTON, May 22 (Reuters) — The House Foreign Affairs Committee on Wednesday voted overwhelmingly to advance a bill that would make it easier for the Biden administration to restrict the export of artificial intelligence systems, citing concerns China could exploit them to bolster its military capabilities.
The bill, sponsored by House Republicans Michael McCaul and John Molenaar and Democrats Raja Krishnamoorthi and Susan Wild, also would give the Commerce Department express authority to bar Americans from working with foreigners to develop AI systems that pose risks to U.S. national security.
Without this legislation “our top AI companies could inadvertently fuel China’s technological ascent, empowering their military and malign ambitions,” McCaul, who chairs the committee, warned on Wednesday.
