Check out all the on-demand sessions from the Intelligent Security Summit here.
Over the last half-decade, quantum computing has attracted tremendous media attention. Why?
After all, we have computers already, which have been around since the 1940s. Is the interest because of the use cases? Better AI? Faster and more accurate pricing for financial services firms and hedge funds? Better medicines once quantum computers get a thousand times bigger?
Check out all the on-demand sessions from the Intelligent Security Summit here.
The metaverse is becoming one of the hottest topics not only in technology but in the social and economic spheres. Tech giants and startups alike are already working on creating services for this new digital reality.
The metaverse is slowly evolving into a mainstream virtual world where you can work, learn, shop, be entertained and interact with others in ways never before possible. Gartner recently listed the metaverse as one of the top strategic technology trends for 2023, and predicts that by 2026, 25% of the population will spend at least one hour a day there for work, shopping, education, social activities and/or entertainment. That means organizations that use the metaverse effectively will be able to engage with both human and machine customers and create new revenue streams and markets.
While it is still unclear how cryptocurrencies will alter in value and where we will be in 2023 — one thing is clear, they are undoubtedly here to stay.
As 2022 draws to a close, the cryptocurrency market is under great scrutiny. From the crypto winter of 2021 that saw Bitcoin lose almost a third of its value and other cryptocurrencies follow suit to security issues with crypto exchanges, bridges, and web 3.0 apps, and of course, FTX’s dramatic failure, it’s almost impossible to disbelieve tales of gloom. However, looking at the forecasts for 2023, it appears the market may rebound, and now may even be an ideal moment to invest.
Da-kuk/iStock.
Improvement in regulation.
A recent study finds that software engineers who use code-generating AI systems are more likely to cause security vulnerabilities in the apps they develop. The paper, co-authored by a team of researchers affiliated with Stanford, highlights the potential pitfalls of code-generating systems as vendors like GitHub start marketing them in earnest.
“Code-generating systems are currently not a replacement for human developers,” Neil Perry, a PhD candidate at Stanford and the lead co-author on the study, told TechCrunch in an email interview. “Developers using them to complete tasks outside of their own areas of expertise should be concerned, and those using them to speed up tasks that they are already skilled at should carefully double-check the outputs and the context that they are used in in the overall project.”
The Stanford study looked specifically at Codex, the AI code-generating system developed by San Francisco-based research lab OpenAI. (Codex powers Copilot.) The researchers recruited 47 developers — ranging from undergraduate students to industry professionals with decades of programming experience — to use Codex to complete security-related problems across programming languages including Python, JavaScript and C.
One afternoon in the fall of 2019, in a grand old office building near the Arc de Triomphe, I was buzzed through an unmarked door into a showroom for the future of surveillance. The space on the other side was dark and sleek, with a look somewhere between an Apple Store and a doomsday bunker. Along one wall, a grid of electronic devices glinted in the moody downlighting—automated license plate readers, Wi-Fi-enabled locks, boxy data processing units. I was here to meet Giovanni Gaccione, who runs the public safety division of a security technology company called Genetec. Headquartered in Montreal, the firm operates four of these “Experience Centers” around the world, where it peddles intelligence products to government officials. Genetec’s main sell here was software, and Gaccione had agreed to show me how it worked.
He led me first to a large monitor running a demo version of Citigraf, his division’s flagship product. The screen displayed a map of the East Side of Chicago. Around the edges were thumbnail-size video streams from neighborhood CCTV cameras. In one feed, a woman appeared to be unloading luggage from a car to the sidewalk. An alert popped up above her head: “ILLEGAL PARKING.” The map itself was scattered with color-coded icons—a house on fire, a gun, a pair of wrestling stick figures—each of which, Gaccione explained, corresponded to an unfolding emergency. He selected the stick figures, which denoted an assault, and a readout appeared onscreen with a few scant details drawn from the 911 dispatch center. At the bottom was a button marked “INVESTIGATE,” just begging to be clicked.
Check out all the on-demand sessions from the Intelligent Security Summit here.
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:
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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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