AI generated visual effects could be a game changer in the film industry. But the emerging field is mired in copyright issues.
Disney is adding another layer to its AI and extended reality strategies. As first reported by Reuters, the company recently formed a dedicated emerging technologies unit. Dubbed the Office of Technology Enablement, the group will coordinate the company’s exploration, adoption and use of artificial intelligence, AR and VR tech.
It has tapped Jamie Voris, previously the CTO of its Studios Technology division, to oversee the effort. Before joining Disney in 2010, Voris was the chief technology officer at the National Football League. More recently, he led the development of the company’s Apple Vision Pro app. Voris will report to Alan Bergman, the co-chairman of Disney Entertainment. Reuters reports the company eventually plans to grow the group to about 100 employees.
“The pace and scope of advances in AI and XR are profound and will continue to impact consumer experiences, creative endeavors, and our business for years to come — making it critical that Disney explore the exciting opportunities and navigate the potential risks,” Bergman wrote in an email Disney shared with Engadget. “The creation of this new group underscores our dedication to doing that and to being a positive force in shaping responsible use and best practices.”
About a year and a half ago, quantum control startup Quantum Machines and Nvidia announced a deep partnership that would bring together Nvidia’s DGX Quantum computing platform and Quantum Machine’s advanced quantum control hardware. We didn’t hear much about the results of this partnership for a while, but it’s now starting to bear fruit and getting the industry one step closer to the holy grail of an error-corrected quantum computer.
In a presentation earlier this year, the two companies showed that they are able to use an off-the-shelf reinforcement learning model running on Nvidia’s DGX platform to better control the qubits in a Rigetti quantum chip by keeping the system calibrated.
Yonatan Cohen, the co-founder and CTO of Quantum Machines, noted how his company has long sought to use general classical compute engines to control quantum processors. Those compute engines were small and limited, but that’s not a problem with Nvidia’s extremely powerful DGX platform. The holy grail, he said, is to run quantum error correction. We’re not there yet. Instead, this collaboration focused on calibration, and specifically calibrating the so-called “π pulses” that control the rotation of a qubit inside a quantum processor.
A recently developed electronic tongue is capable of identifying differences in similar liquids, such as milk with varying water content; diverse products, including soda types and coffee blends; signs of spoilage in fruit juices; and instances of food safety concerns. The team, led by researchers at Penn State, also found that results were even more accurate when artificial intelligence (AI) used its own assessment parameters to interpret the data generated by the electronic tongue.
The researchers published their results today (Oct. 9) in Nature.
According to the researchers, the electronic tongue can be useful for food safety and production, as well as for medical diagnostics. The sensor and its AI can broadly detect and classify various substances while collectively assessing their respective quality, authenticity and freshness. This assessment has also provided the researchers with a view into how AI makes decisions, which could lead to better AI development and applications, they said.
As the AI video wars continue to wage with new, realistic video generating models being released on a near weekly basis, early leader Runway isn’t ceding any ground in terms of capabilities.
With just an iPad, students in any classroom across the world could soon reimagine the ordinary diagrams in any physics textbook—transforming these static images into 3D simulations that run, leap or spin across the page.
A new type of ultrafast memory uses optical signals and magnets to efficiently process and store data.
In 2014, the British philosopher Nick Bostrom published a book about the future of artificial intelligence with the ominous title Superintelligence: Paths, Dangers, Strategies. It proved highly influential in promoting the idea that advanced AI systems—“superintelligences” more capable than humans—might one day take over the world and destroy humanity.
A decade later, OpenAI boss Sam Altman says superintelligence may only be “a few thousand days” away. A year ago, Altman’s OpenAI cofounder Ilya Sutskever set up a team within the company to focus on “safe superintelligence,” but he and his team have now raised a billion dollars to create a startup of their own to pursue this goal.
What exactly are they talking about? Broadly speaking, superintelligence is anything more intelligent than humans. But unpacking what that might mean in practice can get a bit tricky.
DALLAS – Cleaning high-rise windows is an incredibly dangerous job, but artificial intelligence may replace it.
An Israeli-based company launched the U.S. debut of its spider-like robot in North Texas.
It’s not a bird or a plane people watched at the 17Seventeen McKinney building in uptown Dallas.
The question of the conditions under which Artificial Intelligence (AI) can transcend the threshold of consciousness can only be answered with certainty if we manage to unravel the mechanism underlying conscious systems. The most promising strategy to approach this goal is to unveil the brain’s functional principle involved in the formation of conscious states and to transfer the findings to other physical systems. Empirical evidence suggests that the dynamical features of conscious brain processes can be ascribed to self-organized criticality and phase transitions, the deeper understanding of which requires methods of quantum electrodynamics (QED). QED-based model calculations reveal that both the architectural structure and the chemical composition of the brain are specifically designed to establish resonant coupling to the ubiquitous electromagnetic vacuum fluctuations, known as zero-point field (ZPF). A direct consequence of resonant brain-ZPF coupling is the selective amplification of field modes, which leads us to conclude that the distinctive feature of conscious processes consists in modulating the ZPF. These insights support the hypothesis that the ZPF is a foundational field with inherent phenomenal qualities, implying that the crucial condition for AI consciousness lies in a robot’s capacity to tap into the phenomenal spectrum immanent in the ZPF.
Full Title: The Path to Sentient Robots: AI Consciousness in the Light of New Insights into the Functioning of the Brain.
