In particular I like the 3D modeling segment.
Here Dr Seranova talks about stem cell use in helping with research into diseases of aging, particularly generating organiods of the brain by growing them from stem cells.
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Inflection AI just announced Inflection-2, a HUGE new 175 billion parameter language model.
Capabilities exceed Google and Meta’s top models and “is very close” to catching GPT-4.
The CEO also said the company’s next model will be 10x larger in six months.
Inflection AI, the innovative startup behind the conversational chatbot Pi, has recently unveiled a new AI model, Inflection-2, claiming superior performance over popular models developed by Google and Meta. According to a recent Forbes report, this new model is rapidly gaining attention for its potential to rival OpenAI’s GPT-4.
The James Webb Space Telescope has discovered a cosmic ‘peanut’ and ‘fluff ball’ that happen to be two of the four oldest galaxies in the known universe.
Tesla has open-sourced all of the design and engineering of the original Roadster, CEO Elon Musk announced today, and plenty of people are wondering if the timing of the release has anything to do with the next-gen Roadster that is now several years behind schedule.
Tesla has opened everything from Owner’s Manuals to Circuits and Connectors for the original Roadster, which was the automaker’s first project fifteen years ago in 2008.
The vehicle was essentially a fundraising campaign for Tesla as it fought to keep its doors open and transform the passenger vehicle industry. It almost bankrupted the company, but now, everything that was developed for Tesla’s initial EV project is available for anyone to take a look at.
AI can be used to make our lives easier, but it is also a frightening tool that could see many of us out of a job – at least according to some experts.
Australian Academy of Technological Sciences and Engineering (ATSE) CEO Kylie Walker told The Canberra Times AI could replace anywhere between 25 and 46 percent of all Aussie jobs by 2030.
Walker, and a group of 13 other AI experts, called for a $1 billion national artificial intelligence initiative in a new report to push out more than 100,000 digitally skilled workers over the next decade.
Musk said on Thursday that the article headlines will be overlaid at the top because he hates those “giant URL cards.”
Late on Tuesday night, OpenAI announced the return of Sam Altman, its ousted chief executive officer, along with a revamped board that included one name not often associated with Silicon Valley: Larry Summers.
The economist and former Treasury Secretary joined Bret Taylor, a former co-CEO of Salesforce Inc., and existing board member Adam D’Angelo in forming what the company called an “initial board.” OpenAI’s prior directors fired Altman suddenly on Friday, setting off a dramatic saga that cast doubt on the future of the most closely-watched startup and technology.
OpenAI said it was still working to “figure out the details” of its new management in a post online. But with Summers it has a board member with deep ties to Wall Street and Washington — and an adamant belief that artificial intelligence is coming for white-collar jobs.
Experiments with an unconventional superconductor show that a change in the properties of the material’s electrons can, unexpectedly, cause the material to become dramatically less stiff.
Electrons flowing through a crystal lattice don’t usually get to call the shots: their behavior is generally set by the lattice structure. But certain materials exhibit an electron–lattice coupling that allows the conduction electrons to influence the lattice behavior. This electron version of “wagging the dog” is predicted to be quite weak, making it a surprise that experiments with an unconventional superconductor now uncover a large electron-driven softening of the material’s lattice [1]. The finding could provide new insights into the mechanisms underlying unconventional superconductivity.
The lattice in a crystalline material is a periodic framework of atoms held together by electrostatic bonds. That framework dictates the properties of electrons moving through the material. For example, if the lattice is altered by applying mechanical strain or by adding dopant atoms, the electron momenta will correspondingly change, which can affect the material’s electronic band structure.
Numerical simulations reveal that an impact crater’s shape can depend on the impactor’s spin and its degree of cohesion.
Three research groups have exploited the nuclear spins of ytterbium-171 to manipulate qubits before they are read out—an approach that could lead to efficient error-correction schemes for trapped-atom computing platforms.
Quantum computing on neutral-atom platforms has reached remarkable milestones in the past two decades. However, researchers have yet to overcome a key barrier to the realization of a neutral-atom-based quantum computer: the efficient correction of errors. In principle that barrier can be lowered with so-called midcircuit operations. These operations involve probing the quantum state of “ancilla” qubits without disturbing nearby “data” qubits used for computation. The ancilla qubit measurements can indicate whether the data qubits have undergone faulty operations, allowing for the data qubits to be corrected midcircuit—that is, during the execution of the computation rather than after its completion. Now three independent research groups have achieved midcircuit operation, or made progress toward this goal, with a novel choice of atom: ytterbium-171 (171 Yb) [1– 3].
A neutral-atom qubit platform consists of a two-dimensional (2D) array of atoms trapped by optical tweezers—tightly focused laser beams whose wavelengths are tuned far away from the atomic transitions. The size of the traps, limited by diffraction, is typically about 1 µm. Thanks to the large electric-dipole force from the focused laser and to a high vacuum, the atoms can stay trapped for as long as tens of seconds.
