Tesla says it will build new “1st of its kind” data centers. The automaker is hiring staff for it and snapping up some existing data centers.
The data center business is now massive with a market size of more than $250 billion.
Most of the biggest companies in the world, which are known to consumers for other products, are in it, like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and Meta Platforms (Facebook).
The ongoing AI revolution, set to reshape lifestyles and workplaces, has seen deep neural networks (DNNs) play a pivotal role, notably with the emergence of foundation models and generative AI. Yet, the conventional digital computing frameworks that host these models hinder their potential performance and energy efficiency. While AI-specific hardware has emerged, many designs separate memory and processing units, resulting in data shuffling and reduced efficiency.
IBM Research has pursued innovative ways to reimagine AI computation, leading to the concept of analog in-memory computing, or analog AI. This approach draws inspiration from neural networks in biological brains, where synapse strength governs neuron communication. Analog AI employs nanoscale resistive devices like Phase-change memory (PCM) to store synaptic weights as conductance values. PCM devices transition between amorphous and crystalline states, encoding a range of values and enabling local storage of weights with non-volatility.
A significant stride towards making analog AI a reality has been achieved by IBM Research in a recent Nature Electronics publication. They introduced a cutting-edge mixed-signal analog AI chip tailored for various DNN inference tasks. This chip, fabricated at IBM’s Albany NanoTech Complex, features 64 analog in-memory compute cores, each housing a 256-by-256 crossbar array of synaptic unit cells. Integrated compact, time-based analog-to-digital converters facilitate seamless transitions between analog and digital domains. Moreover, digital processing units within each core handle basic neuronal activation functions and scaling operations.
Michio Kaku is the latest expert to shut down AI fears saying the technology is not humanlike at this point.
Thoughts.
Some studies of fish oil supplements have shown a higher risk for atrial fibrillation with marine omega-3 fatty acids. Is it real? What are the implications for patients taking these capsules?
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Shielded by our thick skulls and swaddled in layers of protective tissue, the human brain is extremely difficult to observe in action. Luckily, scientists can use brain organoids — pencil eraser-sized masses of cells that function like human brains but aren’t part of an organism — to look closer. How do they do it? And is it ethical? Madeline Lancaster shares how to make a brain in a lab.
Lesson by Madeline Lancaster, animation by Adam Wells.
New Study Solves Mystery on Insulator-to-Metal Transition
A study explored insulator-to-metal transitions, uncovering discrepancies in the traditional Landau-Zener formula and offering new insights into resistive switching. By using computer simulations, the research highlights the quantum mechanics involved and suggests that electronic and thermal switching can arise simultaneously, with potential applications in microelectronics and neuromorphic computing.
Looking only at their subatomic particles, most materials can be placed into one of two categories.
In a recent narrative review published in BMJ Medicine, researchers summarized the current evidence on advancements in mechanical thrombectomy (MT), a ground-breaking treatment for acute ischaemic stroke involving removal of a thrombus by recanalization of an intracranial occlusion of a large vessel via an aspiration catheter, stent retriever, or both.
Study: Advances in mechanical thrombectomy for acute ischaemic stroke. Image Credit: SewCreamStudio/Shutterstock.com.
The more we like our ideas, the faster we give them shape. But to be creative, we need to focus on out-of-the-box thinking. This is what Alizée Lopez-Persem and Emmanuelle Volle, Inserm researchers at Paris Brain Institute, showed in a new study published in American Psychologist.
Using a behavioral study and a computational model to replicate the different components of the creative process, the researchers explain how individual preferences influence the speed of the emergence of new ideas and their degree of creativity. These preferences also determine which ideas we choose to exploit and communicate to others.
What drives us to develop new ideas rather than settling for standard methods and processes? What triggers the desire to innovate at the risk of sacrificing time, energy, and reputation for a resounding failure? Creativity is based on complex mechanisms that we are only beginning to understand and in which motivation plays a central role. But pursuing a goal is not enough to explain why we favor some ideas over others and whether that choice benefits the success of our actions.
The tiny, floating blobs of mini-hearts were straight out of Frankenstein. Made from a mixture of human stem cells and a sprinkle of silicon nanowires, the cyborg heart organoids bizarrely pumped away as they grew inside Petri dishes.
When transplanted into rats with heart injuries they lost their spherical shape, spreading out into damaged regions and connecting with the hosts’ own heart cells. Within a month, the rats regained much of their heart function.
It’s not science fiction. A new study this month linked digital electrical components with biological cells into a cyborg organoid that, when transplanted into animal models of heart failure, melded with and repaired living, beating hearts.
J. Michael Bailey is a Northwestern University professor of psychology, researcher, and an author known for his work on sexual orientation and human sexuality.
Scientific research has had public scrutiny for a long time. But Michael’s most recent study was placed under so much pressure from upset dissidents that the journal formally retracted it. Today we get to find out just why human sexuality is such a dangerous topic to look into.
