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Hamza Chaudhry

"Although a nuclear confrontation based on fake intelligence may seem unlikely, the stakes during crises are high and timelines are short, creating situations where fake data could well tilt the balance toward nuclear war. "The evolution of nuclear systems has led to further ambiguity in crises and shorter timeframes for verifying intelligence. An intercontinental ballistic missile from Russia could reach the U.S. within 25 minutes. A submarine-launched ballistic missile could arrive even sooner.  "Many modern missiles carry ambiguous payloads, making it unclear whether they are nuclear-tipped. AI tools for verifying the authenticity of content are not sufficiently reliable, making this ambiguity difficult to resolve in a short window. "The likeliest nuclear hotspots are also the arenas involving actors with low levels of trust on both sides — be that the U.S. and the Chinese Communist Party or Russia, or India and Pakistan. Even if communication is established in a...
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Perplexity

The year-old search engine , whose founders previously worked in A.I. research at OpenAI and Meta, has quickly become one of the most buzzed-about products in the tech world. Tech insiders rave about it on social media, and investors like Jeff Bezos — who was also an early investor in Google — have showered it with cash. The company recently announced that it had raised $74 million in a funding round led by Institutional Venture Partners, which valued the company at $520 million. Many start-ups have tried and failed to challenge Google over the years. (One would-be competitor, Neeva, shut down last year after failing to gain traction.)  But Google seems less invincible these days.   Many users have complained that their Google search results have gotten clogged with spammy, low-quality websites, and some people have started looking for answers in places like Reddit and TikTok instead.
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Swarm 🦹‍♂️

"Knowledge discovery from data typically includes solving some type of an optimization problem that can be efficiently addressed using algorithms belonging to the class of evolutionary and bio-inspired computation .  "In this chapter, we give an overview of the various kinds of evolutionary algorithms, such as genetic algorithms, evolutionary strategy, evolutionary and genetic programming, differential evolution, and coevolutionary algorithms, as well as several other bio-inspired approaches, like swarm intelligence and artificial immune systems.  "After elaborating on the methodology, we provide numerous examples of applications in astronomy and geoscience and show how these algorithms can be applied within a distributed environment, by making use of parallel computing, which is essential when dealing with Big Data."
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