To boldly go where no man has gone before. That's the mission of the USS Enterprise -- and arguably the aim of a 1-million prize being offered through a foundation created to honor the father of the "Star Trek" franchise. The Roddenberry Foundation -- named for Gene Roddenberry -- announced Tuesday that this year's biennial award would focus on artificial intelligence that benefits humanity. Lior Ipp, chief executive of the foundation, told The Times there's a growing recognition that AI is becoming more ubiquitous and will affect all aspects of our lives. "We are trying to … catalyze folks to think about what AI looks like if it's used for good," Ipp said, "and what it means to use AI responsibly, ethically and toward solving some of the thorny global challenges that exist in the world."

The robot is shaped like a human, but it sure doesn't move like one. It starts supine on the floor, pancake-flat. Then, in a display of superhuman joint mobility, its legs curl upward from the knees, sort of like a scorpion tail, until its feet settle firmly on the floor beside its hips. From there, it stands up, a swiveling mass of silver limbs. The robot's ring-light head turns a full 180 degrees to face the camera, as though possessed.

With more than 5,000 branches across 48 states and 80 million customers, each with its own unique requirements to satisfy its customers' financial needs, a clear data strategy is key for JPMorgan Chase. According to Mark Birkhead, firm-wide chief data officer at JPMorgan Chase, data analytics is the oxygen that breathes life into the firm to deliver growth and improve the customer experience. Providing first-class business in a first-class way for clients and customers applies to every part of the firm, including its heavy investments in data analytics, machine learning, and AI. Using these advanced technologies, JPMorgan Chase can gain a deeper understanding of the breadth and specificity of the needs of the customers and communities it serves. "It means using our data to drive positive outcomes for our customers and our clients and our business partners. And it means using this to actually help our customers and clients manage their daily lives in a better, simpler way," says Birkhead.

The journey toward successfully deployed machine learning operations (MLOps) starts with data, says global head of machine learning operations and platforms at Kraft Heinz Company, Jorge Balestra. Curating well-organized and accessible data means enterprises can leverage their data volumes to train and develop AI and machine learning models. A strong data strategy lays the foundation for these AI and machine learning tools to use data to detect supply chain disruptions, identify and address cost inefficiencies, and predict demand for products. "Never forget that data is the fuel, and data, it takes effort, it is a journey, it never ends, because that's what is really what I would call what differentiates a lot of successful efforts compared to unsuccessful ones," says Balestra. This is especially crucial but challenging within the CPG sector where data is often incomplete given the inconsistent methods for consumer habit tracking among different retailers.

Winnow CEO Marc Zornes and Iberostar Group's Dr. Megan Morikawa discuss how artificial intelligence can target food waste in commercial kitchens -- and improve both business efficiency and global sustainability. Food waste makes up an estimated 30% to 40% of the food supply, according to the U.S. Department of Agriculture -- and now a London company is using artificial intelligence in an attempt to address the problem. Winnow, a food waste solution company, has developed an AI-powered system that aims to reduce food waste in commercial kitchens worldwide. CEO Marc Zornes said the company's tech can measure the foods that get tossed daily using machine learning and a camera. "We use computer vision to identify what's being wasted in real time, literally as the food's being thrown away," he told Fox News Digital in an interview.

Center for A.I. Safety Director Dan Hendrycks explains concerns about how the rapid growth of artificial intelligence could impact society. House lawmakers are urging federal agencies to quickly and aggressively adopt artificial intelligence technology, at a time when the push from civil rights and industry groups for new AI regulations is still waiting to get off the ground. The House Appropriations Committee, led by Rep. Kay Granger, R-Texas, released several spending bills this week that encourage the government to incorporate AI into everything from national security functions to routine office work to the detection of pests and diseases in crops. Several of those priorities are not just encouraged but would get millions of dollars in new funding under the legislation still being considered by the committee. And while comprehensive AI regulations are likely still months away and are unlikely to be developed this year, lawmakers seem keen on making sure the government is deploying AI where it can. The bills are backed by the GOP majority, and Rep. Don Beyer, D-Va., the vice chair of the Congressional Artificial Intelligence Caucus, said agencies shouldn't have to wait to start using AI.

As a CTO with over a decade and a half of experience in the ever-changing field of cybersecurity, I've witnessed the enormous impact that artificial intelligence (AI) has had on the broad technological landscape. In addition, I have seen how AI-based solutions have emerged as an important aspect of improving processes in a variety of fields and disciplines over the years. The capacity of AI-based machine learning (ML) models to recognize patterns and make data-driven decisions and inferences represents a highly innovative strategy for rapidly identifying malware, directing incident response, and even anticipating potential security breaches. AI's role in cybersecurity, how it can be used to improve corporate and user security, and its limitations. Data is being generated at an exponential rate in the modern era of digitization, and an increasing amount of metadata is being saved or received online, either directly or indirectly. Furthermore, in order for data to reach its intended location or be used for specific purposes, it is frequently necessary to send it across a network or store it in a specific database or server.

Low-code and no-code platforms are used to build applications, websites, mobile apps, forms, dashboards, data pipelines, and integrations. No-code platforms help business users, sometimes termed citizen developers, to migrate from spreadsheets, extend beyond email collaborations, and transition from manual task execution to using tools and automations across departments. Low-code platforms are usually for technologists and provide ways to deliver and support software with little or no coding. "You have to remember low code is just a fancy term for abstraction. We are abstracting away non-essential elements in order to simplify the user experience," says Gordon Allott, President and CEO of K3.

A trickle of AI-fueled misinformation has turned into a powerful stream over the past year, with fake photos and videos--from Donald Trump's and Vladimir Putin's "arrest" to the Pope's "gangsta" outfit--highlighting the scope of the problem. "Deepfake" is an umbrella term for various types of synthetic content, created or altered with the aid of artificial intelligence, which can appear to show events, scenes or conversations that never happened. These types of creations come in a variety of visual, audial, and textual forms and can feature something innocuous, such as Jim Carrey in The Shining, or far more sinister and dangerous--like the fake videos of Joe Biden's "address to the nation," for example. Initially, deepfake technology was largely used to generate pranks and involuntary pornography. Now, it is increasingly deployed as a vehicle for misinformation--scientific, medical, financial, and, perhaps most worryingly, political. Newsweek previously reported on warnings that these technologies already present a real threat and have the potential to upend the democratic process in the 2024 election, with calls growing louder for regulators, big tech, and governments to intervene.

One of the areas where technology law is likely to see development in South Africa is the regulation of data privacy. The Protection of Personal Information Act (PoPIA) protects personal information and regulates the processing of personal data. However, with the rise of big data and the increasing use of technology in various industries, the legal framework surrounding data privacy will likely evolve in the coming years. This may include changes to PoPIA itself, as well as new legislation and case law that addresses emerging issues in data protection. Another area where tech law will likely see development is regulating artificial intelligence (AI) and machine learning.