Samsung unveiled AI-powered products at CES 2026: Everything announced from the year's first press conference CES 2026 kicked off with a big press conference from one of the biggest companies at the show: Samsung. The tech giant held its first look presentation to show off new home products and make a plethora of AI-infused announcements. New TVs, speakers, projectors and more were among the headliners, along with updated gaming monitors and soundbars. Many of the products announced on stage were not actually new, but instead had been dripped out by Samsung recently. We did get a closer look a previously undisclosed set, a flagship 130-inch Micro RGB TV framed by a giant metal easel with embedded speakers.

Google is said to be in panic mode over ChatGPT. The company is reportedly preparing to show off at least 20 AI-powered products and a chatbot for its search engine this year, with at least some set to debut at its I/O conference in May. Google reportedly sees ChatGPT as a threat to its business and has sped up development of AI-powered products. Google said AI would be its focus while announcing the layoffs of 12,000 employees this morning, and a report by The New York Times highlights plans to use the tech for search, image generation, and other new products.

Data labeling: One way to make money with AI is by working as a data labeler. This involves preparing data sets that are used to train machine learning models. Data labelers are responsible for reviewing data and assigning labels to it so that the model can learn to recognize patterns and make predictions. AI consulting: Another way to make money with AI is by offering consulting services to businesses that are looking to implement AI solutions. This could involve helping businesses identify the best AI tools and techniques to use for their specific needs, as well as providing guidance on how to implement and manage AI projects.

You are looking for that next big bet. Artificial Intelligence (AI) seems to be the hottest thing in town. You're also aware that healthcare is ripe for transformation through digital innovation. That is why you made time to be a judge at that pitch fest which has just kicked off. Ten seconds into the first pitch, you have heard the terms "AI," "data" and "healthcare."

TLDR; Machine learning models are only as good as the data (features) they are trained on. In enterprises, data scientists can often train very effective models in the lab - when given a free hand on which data to use. However, many of those data sources are not available in production environments due to disconnected systems and data silos. An AI-powered product that is limited to the data available within its application silo cannot recall historical data about its users or relevant contextual data from external sources. It is like a jellyfish - its autonomic system makes it functional and useful, but it lacks a brain.

At LinkedIn, our guiding principle is "Members First." It ensures we honor our responsibility to protect our members and maintain their trust in every decision we make, and puts their interests first. A key area where we apply this value in engineering is within our design process. We call this "responsible design," which means that everything we build is intended to work as part of a unified system that delivers the best member experience, provides the right protections for our members and customers, and mitigates any unintended consequences in our products. One of the core pillars of "responsible design" is "responsible AI," which follows Microsoft's Responsible AI Principles.

The use of technology in daily life is nothing to be surprised about. But oftentimes, we await a future where AI-products fill our space, forgetting how much it has already invaded our routine. AI-powered products are already taking over our lives for good. Even though we anticipate the importance of technology in daily life at maximum is a few years away, they are already causing considerable effects and have big impacts on us. The phrase'technology in daily life' may sound intimidating to some, but it has been in use for decades and its applications are more common than you might imagine.

There has been a lot of talk in the recent years about the use of AI capabilities or machine-learned solutions to improve digital products or services and user experience. If we can cut through the hype and have the necessary building blocks in place as covered in Four Hurdles To Creating Value From Data, there is legitimate value to be had from the use of data and AI to make better products in many verticals. For tech companies that are founded on strong engineering practices and find themselves knee deep in data such as Uber, Twitter and Tesla, the use of AI techniques to extract value is likely to be already part of their culture. As for others facing a different set of circumstances and yet, still see the need to adopt data and AI to remain competitive, these companies may not know where to start or underestimate the changes that are involved. The previous CEO of GE, Jeff Immelt shared from his experience during the digitization of the industrial world, that the transformation involved more than just software and technology people.

For tech enthusiasts who are interested in solving fundamental science, puzzles are provided with a globally distributed platform – Microsoft Research. The programs undertaken for the organization often focus on disruptive technologies like machine learning and artificial intelligence. With its mission to underpin AI smarts in all of its products, the company is also seeking ways to merge innovations by Microsoft Research in the rest of the company. In every certain way, the company is trying to become more and more innovative especially around its work concerning AI. Microsoft is also putting processes into place to attain such innovation. The company is usually open about its processes and this year at Ignite, its focus was on such innovations only.

For tech enthusiasts who are interested in solving fundamental science, puzzles are provided with a globally distributed platform – Microsoft Research. The programs undertaken for the organization often focus on disruptive technologies like machine learning and artificial intelligence. With its mission to underpin AI smarts in all of its products, the company is also seeking ways to merge innovations by Microsoft Research in the rest of the company. In every certain way, the company is trying to become more and more innovative especially around its work concerning AI. Microsoft is also putting processes into place to attain such innovation. The company is usually open about its processes and this year at Ignite, its focus was on such innovations only.