A young entrepreneur who was among the earliest known recruiters for Elon Musk's so-called Department of Government Efficiency (DOGE) has a new, related gig--and he's hiring. Anthony Jancso, cofounder of AcclerateX, a government tech startup, is looking for technologists to work on a project that aims to have artificial intelligence perform tasks that are currently the responsibility of tens of thousands of federal workers. Jancso, a former Palantir employee, wrote in a Slack with about 2000 Palantir alumni in it that he's hiring for a "DOGE orthogonal project to design benchmarks and deploy AI agents across live workflows in federal agencies," according to an April 21 post reviewed by WIRED. Agents are programs that can perform work autonomously. "We've identified over 300 roles with almost full-process standardization, freeing up at least 70k FTEs for higher-impact work over the next year," he continued, essentially claiming that tens of thousands of federal employees could see many aspects of their job automated and replaced by these AI agents.

AI-enabled management platforms and infrastructure are beginning to make their way into enterprise networks. I say "beginning" because despite lots of AI-washing marketing efforts over the last few years, a lot of what has been characterized as "AI-driven" or "powered by AI" hasn't really materialized. It's not that these systems don't do what the marketers say, so much as they don't do it in the way they imply. Even some tools that do truly employ AI in meaningful ways, and with visibly different results than are possible without it, don't feel qualitatively different from what has come before. They may be better, for example by dramatically reducing the number of false positives in alert traffic, but not different.

Replacing human agents with AI chatbots could save the call centre industry up to $80bn in labour costs per year by 2026 and $240bn by 2031, according to a new report by Gartner which also predicts $1.99bn will be spent by the sector on AI this year alone. The report predicts that the number of interactions between customers and a call centre handled by AI will go from 2% in 2022 to more than 15% by 2026, and double to 30% by 2031. About 17 million contact centre agents are working around the world today with 95% of costs associated with a call centre due to staffing. Daniel O'Connell, VP analyst for Gartner and author of the report, says that organisations are both struggling to recruit and needing to reduce those costs. "Conversational AI makes agents more efficient and effective, while also improving the customer experience," he said.

New York (CNN Business)The machines are officially winning. Investors who've relied on a standard 60/40 portfolio this year have taken a bath as stocks and bonds have tumbled. Even gold, the go-to safe haven in volatile times, is underperforming. But for a small subset of specialized hedge funds known as quants, the chaos of 2022 has unleashed a windfall. While the S&P 500 is down more than 13% this year, quant hedge funds -- which rely on complex mathematical models to make investing decisions -- are up more than 15%, according to HFR, a hedge fund research group.

The "machine–learning" patrol model analyzed more than 6 million officer responses to nearly 2 million calls for service, the Greater Austin Crime …

Every company worth its weight is set on achieving practical and scalable artificial intelligence and machine learning. However, it's all much easier said than done -- to which AI leaders within some of the most information-intensive enterprises can attest. For more perspective on the challenges of building an AI-driven organization, we caught up with Jing Huang, senior director of engineering and machine learning at Momentive (formerly SurveyMonkey), who shares the lessons being learned as AI and ML are rolled out. Q: AI and machine learning initiatives have been underway for several years now. What lessons have enterprises been learning in terms of most productive adoption and deployment?

Traditional endpoint protection is reactive, responding once something has happened. Endpoint protection with machine learning is proactive, capable of studying an almost limitless amount of network traffic, logging information and app installations for anomalous activity. "Security technologies with artificial intelligence capabilities have the potential to anticipate attacks and counter them in real-time," says Turner. "Given that cyberattacks occur in seconds, the speed brought by AI-driven security technologies is crucial." Because of the recent shift to remote learning, the number of endpoints has exploded.

Here's a guide to staff your Artificial intelligence – seems like there is no stopping it. There are millions of articles on the web and many on our website which talk in-depth about how revolutionary AI is. The sheer diversity and complexity of AI projects at times like now where rapid production is required to meet the pandemic demands are creating a need to identify key AI roles and finding the right personnel for the job. Organizations face challenges in leveraging artificial intelligence projects due to the lack of required skills, collaboration, tools, and the ability to create and manage a dynamic, production-level AI pipeline. According to Gartner, by 2023, 50% of IT leaders will find it tough to move their artificial intelligence products past proof of concept (POC) to a production-grade maturity.

Over 80% of executives currently believe that artificial intelligence has the ability to improve both productivity and performance. I am one of those executives. I have directed my company to fully embrace the AI-assisted staffing trend. We are so committed to this initiative that we recently built our own proprietary AI staffing platform that is currently in beta testing. I have personally experienced how AI is changing staffing and recruiting for the better.

When you think of artificial intelligence, you might think of examples from science fiction like Terminator or The Matrix. Modern AI exists without the limitations that you see in movies, operating on everything from the smartphones in your pocket to the website that uses machine learning to track COVID-19. Artificial intelligence was designed to solve for specific tasks and has applications that can dramatically impact the bottom line in your restaurant, from automating features to the burger-flipping robots of the future. As we look into an uncertain future, the opportunities to employ artificial intelligence to automate your restaurant is an excellent way to put AI to work for you. As the coronavirus has taught us, a robust communications network is critical to ensuring that everyone is kept aware of changes.