As digital scamming explodes in Southeast Asia, including so called "pig butchering" investment scams, the United Nations Office on Drugs and Crime (UNODC) issued a comprehensive report this week with a dire warning about the rapid growth of this criminal ecosystem. Many digital scams have traditionally relied on social engineering, or tricking victims into giving away their money willingly, rather than leaning on malware or other highly technical methods. But researchers have increasingly sounded the alarm that scammers are incorporating generative AI content and deepfakes to expand the scale and effectiveness of their operations. And the UN report offers the clearest evidence yet that these high tech tools are turning an already urgent situation into a crisis. In addition to buying written scripts to use with potential victims or relying on templates for malicious websites, attackers have increasingly been leaning on generative AI platforms to create communication content in multiple languages and deepfake generators that can create photos or even video of nonexistent people to show victims and enhance verisimilitude.

Sammy Selim strode through the dense, shiny green bushes on the slopes of his coffee farm in Sorwot village in Kericho, Kenya, accompanied by a younger farmer called Kennedy Kirui. They paused at each corner to input the farm's coordinates into a WhatsApp conversation. The conversation was with Virtual Agronomist, a tool that uses artificial intelligence to provide fertiliser application advice using chat prompts. The chatbot asked some further questions before producing a report saying that Selim should target a yield of 7.9 tonnes and use three types of fertiliser in specific quantities to achieve that goal. "My God!" Selim said upon receipt of the report.

Papalambrou, who works at the University's School of Naval Architecture and Marine Engineering, says the custom-made monitoring system -- with solar power, recognition software and luminosity-triggered lens wipers to unclog debris -- could be a template deployed to other underwater sites.

One of the biggest understatements that can be made is that automotive production operations--say an engine plant--are highly complex networks of people, machinery, controls, communications, and work in various states of process. Take the FCA Trenton Engine Complex. It is even called "complex" in its name. This is a two-facility operation, There is Trenton South. It covers some 822,000 square feet.

The "2020 Global Forecast for Artificial Intelligence (Ai) Chipsets (2021-2026 Outlook)-High Tech & Emerging Markets Report" report has been added to ResearchAndMarkets.com's offering. This report contains timely and accurate market statistics and forecasts on the market for over 140 countries. Published annually, it provides a unique and accurate estimate on market sizing for this equipment/material using a proprietary economic model that integrates historical trends (horizontal analysis) and longitudinal analysis of incorporated industries (vertical analysis). Estimates on equipment or material sales (product shipments value) are published historically for 2013 to 2017, projections for 2016 to 2020 and forecasts for 2021 to 2026. Product shipments include the total value of all products produced and shipped by all producers.

Las Vegas-based Konami Gaming, Inc. is developing a facial recognition system for casino gaming. Using a biometric welcome console guests approach the device and within seconds the system greets them and logs them in, allowing them to play.

The high-tech industry has been a leading adopter of artificial intelligence (AI), so much so that it influences the digital transformation trends in most other industries. Technology giants are not just building AI solutions, they are acquiring smaller AI companies to build more capabilities and finding new use cases outside the IT department, in our offices, hospitals, and homes. Yet, as per leading research reports these firms are still lagging in the overall AI adoption when compared with other digitization efforts. This paper attempts to find the factors behind the high-tech industry's failure to scale and the best practices the industry can adopt to encourage mainstream adoption. It has been almost seven decades since Alan Turing first envisioned a'thinking' machine that could potentially carry on a conversation with a human that was indistinguishable from a human-to-human interaction. Since then, AI has seen several periods of crests and troughs.

President Xi Jinping's "Made in China 2025" strategy, unveiled in 2015 and now thrust back into the limelight by President Trump's bellicose stance on trade, holds three important lesson for global industry. This should be a non-controversial statement, but it is not. Economists often mock "the manufacturing fetish" and argue there is no reason to consider manufacturing a better driver of economic growth than any other sector. As economies get richer, they tend to shift from agriculture to industry, and then to services. Manufacturing accounted for nearly 30% of the U.S. economy in the 1950s; it was still 20% in the 1980s; today it accounts for just 11%.

Retiring well & aging independently requires more than health and wealth, it requires a supportive community. On an extraordinarily hot Independence Day weekend, I visited my elderly mother-in-law in her quiet suburban community on the edge of Boston, Massachusetts. She lives alone and mostly independently. Part of my wife's and my weekend ritual is visiting and running errands with her. As we walked down her driveway, we saw a black car drive slowly down the quiet, empty street. A man stuck his head out the window and asked whether I had seen an older Asian man dressed in dark clothing walking through the neighborhood.

Recruiters have always been prized for their ability to work with people. Now, they're starting to work with robots, too. As artificial intelligence has found its place in the industry, helping source, screen, schedule and interview candidates, recruiters have taken on newer, more important roles in their companies than ever before. Rather than focusing solely on the upfront tasks of finding and onboarding talent, AI has freed them up to concentrate on later-stage issues like ensuring candidate success. AI promises to deliver higher quality candidates by analyzing data patterns that might have otherwise gone unnoticed to human recruiters.