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It’s as good a time as any to discuss the implications of advances in artificial intelligence (AI). 2022 saw interesting progress in deep learning, especially in generative models. However, as the capabilities of deep learning models increase, so does the confusion surrounding them.
On the one hand, advanced models such as ChatGPT and DALL-E are displaying fascinating results and the impression of thinking and reasoning. On the other hand, they often make errors that prove they lack some of the basic elements of intelligence that humans have.
Check out all the on-demand sessions from the Intelligent Security Summit here.
Tomorrow morning, I head south. Straight down I-95, from central New Jersey to northeast Florida, where I will be setting up my laptop in St. Augustine for the next two months. It’s about as far from Silicon Valley as I can be in the continental U.S., but that’s where you’ll find me gearing up for the first artificial intelligence (AI) news of 2023.
These are the 5 biggest AI stories I’m waiting for:
Nearly 70 years after having his security clearance revoked by the Atomic Energy Commission (AEC) due to suspicion of being a Soviet spy, Manhattan Project physicist J. Robert Oppenheimer has finally received some form of justice just in time for Christmas, according to a December 16 article in the New York Times. US Secretary of Energy Jennifer M. Granholm released a statement nullifying the controversial decision that badly tarnished the late physicist’s reputation, declaring it to be the result of a “flawed process” that violated the AEC’s own regulations.
Science historian Alex Wellerstein of Stevens Institute of Technology told the New York Times that the exoneration was long overdue. “I’m sure it doesn’t go as far as Oppenheimer and his family would have wanted,” he said. “But it goes pretty far. The injustice done to Oppenheimer doesn’t get undone by this. But it’s nice to see some response and reconciliation even if it’s decades too late.”
Oppenheimer was born in New York City to German Jewish immigrants and studied physics under Ernest Rutherford at Cambridge, before earning his PhD from the University of Gottingen in 1927 under Max Born. He eventually joined the faculty at the University of California, Berkeley. When President Franklin D. Roosevelt approved the Manhattan Project and tapped Major General Leslie R. Groves to head it, Groves in turn chose Oppenheimer to lead the secret weapons laboratory in Los Alamos, New Mexico. True, Oppenheimer had left-wing political views, and hadn’t won a Nobel Prize (although he was nominated several times). But Groves felt the physicist had the breadth of knowledge to bring together physicists, chemists, engineers, and metallurgists, among other disciplines whose expertise would be crucial to the success of the project.
As computer scientists tackle a greater range of problems, their work has grown increasingly interdisciplinary. This year, many of the most significant computer science results also involved other scientists and mathematicians. Perhaps the most practical involved the cryptographic questions underlying the security of the internet, which tend to be complicated mathematical problems. One such problem — the product of two elliptic curves and their relation to an abelian surface — ended up bringing down a promising new cryptography scheme that was thought to be strong enough to withstand an attack from a quantum computer. And a different set of mathematical relationships, in the form of one-way functions, will tell cryptographers if truly secure codes are even possible.
Computer science, and quantum computing in particular, also heavily overlaps with physics. In one of the biggest developments in theoretical computer science this year, researchers posted a proof of the NLTS conjecture, which (among other things) states that a ghostly connection between particles known as quantum entanglement is not as delicate as physicists once imagined. This has implications not just for our understanding of the physical world, but also for the myriad cryptographic possibilities that entanglement makes possible.
China’s ByteDance is using data from TikTok to track journalists and this is now raising eyebrows. There is growing fears that security concerns over TikTok might actually be true. The Chinese ByteDance wants to know which of its employees are speaking to the media.
#china #tiktok #bytedance.
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Face recognition tools are computational models that can identify specific people in images, as well as CCTV or video footage. These tools are already being used in a wide range of real-world settings, for instance aiding law enforcement and border control agents in their criminal investigations and surveillance efforts, and for authentication and biometric applications. While most existing models perform remarkably well, there may still be much room for improvement.
Researchers at Queen Mary University of London have recently created a new and promising architecture for face recognition. This architecture, presented in a paper pre-published on arXiv, is based on a strategy to extract facial features from images that differs from most of those proposed so far.
“Holistic methods using convolutional neural networks (CNNs) and margin-based losses have dominated research on face recognition,” Zhonglin Sun and Georgios Tzimiropoulos, the two researchers who carried out the study, told TechXplore.
Check out all the on-demand sessions from the Intelligent Security Summit here.
Simulation can help engineers overcome these challenges. Rather than tweaking the AI model’s architecture and parameters, it has been shown that time spent improving the training data can often yield more extensive improvements in accuracy.
Check out all the on-demand sessions from the Intelligent Security Summit here.
The adoption of a password-free future is hyped by some of the biggest tech companies, with Apple, Google, and Microsoft committing to support the FIDO standard this past May. Along with the Digital ID Bill reintroduced to Congress this past July, we’re poised to take a giant leap away from the password to a seemingly more secure digital future. But as we approach a post-password world, we still have a long way to go in ensuring the security of our digital lives.
As companies continue developing solutions to bridge us to a passwordless world, many have prioritized convenience over security. Methods of two-factor authentication (2FA) and multi-factor authentication (MFA) such as SMS or email verification — or even the use of biometrics — have emerged as leading alternatives to the traditional username/password. But here’s the catch: Most of these companies are validating devices alone and aren’t properly leveraging this technology, leaving the door open for bad actors.
Check out all the on-demand sessions from the Intelligent Security Summit here.
With the arrival of AI-generated art and the proliferation of tools like Midjourney, Stable Diffusion and DALL-E, questions have been rife in circles across the creative industry.
Is this a temporary trend? Or a would-be essential tool in creative communication?
