Tesla’s success and potential for “Total Domination” in the automotive industry is driven by their advanced technology and their ability to revolutionize vehicle production.
Questions to inspire discussion.
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Mismatch repair deficiency is a biomarker for predicting response to cancer immune checkpoint inhibitors. A new study may explain why it can fall short.
In just one year, artificial intelligence has gone from being the stuff of science fiction movies to being used as a tool to help us polish our resumes and plan European getaways.
Although generative AI models may be capable of writing emails and reviewing code, these tech experts don’t see them replacing humans any time soon. Here’s why.
The chatbot’s summarization feature relies on preprocessed video data or existing subtitles and transcripts.
One feature added to Microsoft’s AI Copilot in the Edge browser this week is the ability to generate text summaries of videos.
It leans on text from subtitles and transcriptions.
Continue reading “Microsoft’s Edge Copilot AI can’t really summarize every YouTube video” »
NotebookLM is also getting a feature that transforms your notes into another type of document.
NotebookLM got an upgrade.
Engineers and major companies are pushing a technology called L4S that they say could make the web feel dramatically faster.
L4S could fix a problem that even gigabit connections don’t.
Most space heaters run electricity through high resistance wires to toast your toes. The Heatbit mini, however, trains large language models, builds AI for large corporations, or mines crypto while it warms up your home. In so doing, it pays its owners up to $28/month while in use.
“What we really do is zero-energy computing,” says CEO Alex Busarov, who I met at Web Summit in Lisbon recently.
Bitcoin mining and AI training—which has increased one million times over the last seven years—together consume more energy than the entire United Kingdom, Busarov says. All of that goes to waste as heat, which then itself often needs to be cooled in a data or compute center, costing yet more energy.
The recent drama at OpenAI, where CEO Sam Altman was briefly dismissed by the board of directors only to be rapidly reinstated, has sparked discussion about the company prioritizing profits over its original nonprofit mission.
In fact, no company is purely profit-driven, nor should they be. While profits are paramount to survival in the competitive marketplace, they should always be pursued with a degree of social responsibility. What that means will of course vary from person to person and context to context. Still, profits act like a guardrail that prevents managers of organizations from over-indulging their passions. OpenAI’s strict reversal in recent weeks is a clear-cut example of this.
The embrace of capitalism and the pursuit of profits is not just a pragmatic choice to satisfy investors. It will make OpenAI better at achieving its mission of safe and responsible AI, by curtailing the worst excesses of those with power within the company. In a world where artificial intelligence may hold the key to our future, profit isn’t just good, it’s essential for ensuring progress stays on track and remains ethical.
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AMD provided a deep-dive look at its latest AI accelerator arsenal for data centers and supercomputers, as well as consumer client devices, but software support, optimization and developer adoption will be key.
Advanced Micro Devices held its Advancing AI event in San Jose this week, and in addition to launching new AI accelerators for the data center, supercomputing and client laptops, the company also laid out its software and ecosystem enablement strategy with an emphasis on open source accessibility. Market demand for AI compute resources is currently outstripping supply from incumbents like Nvidia, so AMD is racing to provide compelling alternatives. Underscoring this emphatically, AMD CEO Dr. Lisa Su, noted that the company is raising its TAM forecast for AI accelerators from the $150 billion number it projected a year ago at this time, to $400 billion by 2027 with a 70% compounded annual growth rate. Artificial Intelligence is obviously a massive opportunity for the major chip players, but it’s really anybody’s guess as to the true potential market demand. AI will be so transformational that it will impact virtually all industries in some way or another. Regardless, the market will likely be welcoming and eager for these new AI silicon engines and tools from AMD.
AMD’s data center group formally launched two major product family offerings this week, known as the MI300X and MI300A, for the enterprise and cloud AI and supercomputing markets, respectively. These two products are purpose-built for their respective applications, but are based on similar chiplet-enabled architectures with advanced 3D packaging techniques and a mix of optimized 5 and 6nm semiconductor chip fab processes. AMD’s High Performance Computing AI accelerator is the Instinct MI300A that is comprised of both the company’s CDNA 3 data center GPU architecture, along with Zen 4 CPU core chiplets (24 EPYC Genoa cores) and 128GB of shared, unified HBM3 memory that both the GPU accelerators and CPU cores have access to, as well as 256MB of Infinity Cache. The chip is comprised of a whopping 146B transistors and offers up to 5.3 TB/s of peak memory bandwidth, with its CPU, GPU, and IO interconnect enabled via AMD’s high speed serial Infinity Fabric.
Continue reading “AMD Unveils AI Accelerators From Cloud To Client With MI300 Leading The Charge” »
