CES 2026 kicked off Sunday, January 4th, with the annual “CTA Tech Trends to Watch” presentation for members of media, hosted by Melissa Harrison, VP communication & marketing, CTA, and Brian Comiskey, senior director, Innovation & Trends, CTA.
Innovation doesn’t happen in isolation. Breakthroughs rarely stay confined to a single sidewalk, industry, or discipline. Instead, progress emerges where technologies intersect—where advances in one field accelerate transformation in another. Because of this interdependence, the most impactful technologies are never just one thing.
Today’s wave of innovation can be understood through three major megatrends: Intelligent Transformation, Longevity, and Engineering Tomorrow. Together, they are redefining how we live, work, and build the future.
1. Intelligent Transformation: Beyond Digital
For the past two decades, digital transformation shaped enterprises and economies. Cloud computing, mobile connectivity, and digital platforms redefined how businesses operate and how consumers engage with the world. This era enabled scale, lowered barriers to entry, and connected billions globally.
Now, we have entered a new phase: intelligent transformation.
Driven by rapid advances in artificial intelligence, intelligent transformation goes beyond digitizing processes. It embeds intelligence directly into systems, devices, and infrastructure—reshaping enterprise operations, workforce roles, and everyday consumer experiences at massive scale.
The Foundations of Intelligence
This transformation rests on three critical pillars:
Trust and Security Modern cybersecurity ensures data integrity, encrypted communication, and resilience against threats. Without trust, intelligent systems cannot scale. Secure infrastructure enables innovation to move faster and farther.
Scalable Cloud Infrastructure Hyperscale platforms allow AI to operate globally and elastically. From startups to multinational enterprises, cloud scalability ensures intelligent capabilities are accessible across industries and geographies.
Computation and Simulation Intelligence begins at the chip level. Advanced processors and simulation technologies transform raw data into actionable insight, enabling faster, smarter decision-making across every sector.
AI at Work and in Industry
AI has moved from experimentation to necessity. Across global markets, awareness and adoption exceed critical thresholds. Workers are already reclaiming hours each week through AI-assisted productivity, signaling a shift toward human–AI collaboration rather than replacement.
Industries such as healthcare, mobility, agriculture, logistics, and manufacturing are adopting industrial AI, embedding intelligence directly into infrastructure and operations. These systems improve productivity, resilience, and scalability—allowing complex industrial environments to function as connected, adaptive ecosystems.
Physical AI and Robotics
The rise of physical AI—robots and autonomous systems—marks another leap forward. Consumer, healthcare, and industrial robots are gaining contextual awareness, enabling them to perform increasingly complex tasks. Autonomous vehicles, warehouse robots, and service robots are learning to navigate real-world environments safely and efficiently.
Extended reality (XR), smart glasses, and voice-driven interfaces further blur the boundary between digital and physical worlds. These technologies enhance human capability across healthcare, logistics, manufacturing, and hospitality—making intelligence tangible and interactive.
2. Longevity: Redefining Quality of Life
While intelligent systems transform productivity, longevity technologies redefine what progress means. The new measure of advancement is no longer just economic growth—but longer, healthier, higher-quality lives.
Precision Health and Personalized Care
Healthcare is shifting from reactive, one-size-fits-all treatment to precision medicine. Advances in genomics, AI-driven diagnostics, and biological modeling enable early detection, predictive insights, and tailored interventions.
Connected wearables, remote diagnostics, and telehealth platforms extend care beyond hospitals, allowing continuous, proactive health management. Individuals increasingly become active participants—executives of their own health—empowered by real-time data and personalized insights.
From Treatment to Prevention
Health technology ecosystems now integrate glucose monitors, digital stethoscopes, cardiovascular sensors, and AI-powered health platforms. These tools reduce strain on healthcare systems while improving outcomes through early intervention and continuous monitoring.
Mental health is also evolving, with AI-driven tools identifying early signals of stress, anxiety, and depression, and providing scalable, accessible support through conversational and behavioral technologies.
Human-Centered Enhancement
Longevity innovation extends beyond health into accessibility and inclusion. Exoskeletons, advanced hearing solutions, neuro-responsive interfaces, and assistive technologies enhance mobility, sensory perception, and quality of life—ensuring progress benefits broader populations.
3. Engineering Tomorrow: Building Sustainable Systems
The third transformation focuses on how technology reshapes the physical world—engineering tomorrow’s infrastructure, mobility, energy, and production systems.
Intelligent Mobility
Vehicles are no longer static machines. They are becoming software-defined platforms with over-the-air updates, personalization, predictive maintenance, and autonomous capabilities. Automakers increasingly collaborate with cloud providers, AI developers, and content platforms to accelerate innovation.
Autonomous driving systems, advanced sensing technologies, and human–machine interfaces are improving safety, accessibility, and efficiency—turning transportation into a connected, intelligent ecosystem.
Smart Industry and Agriculture
AI-powered heavy equipment, autonomous construction systems, and precision agriculture technologies are redefining productivity while reducing environmental impact. Autonomous tractors, predictive analytics, and vertical farming systems enhance food security and sustainability in the face of climate and labor challenges.
Energy and Electrification
Electrification is accelerating across industries. Smart grids, adaptive solar systems, energy storage, and AI-driven demand optimization are transforming how energy is generated, distributed, and consumed. Emerging technologies—including advanced nuclear and alternative energy systems—promise resilient, low-carbon infrastructure for the future.
The Road Ahead
By 2026 and beyond, intelligent transformation will drive autonomous systems, adaptive devices, and deeply personalized experiences. Smartphones, PCs, TVs, vehicles, and wearables are evolving into intelligent platforms that respond dynamically to individual needs.
Together, intelligent transformation, longevity innovation, and engineering tomorrow are converging to solve some of the world’s biggest challenges—improving productivity, extending healthy lifespans, and building resilient, sustainable systems.
Innovation doesn’t occur in isolation. It happens at the intersections—and those intersections are shaping the future now.
Imec closed out 2025 with significant announcements that underscore its growing influence in semiconductor R&D and AI systems design. Between a high-profile debut at Super Computing 2025 and a strong showing at the International Electron Devices Meeting (IEDM), the Belgium-based research center marked the end of the year with momentum across multiple technology fronts.
In November at Super Computing 2025, one of the world’s largest gatherings for high-performance computing, imec unveiled imec.kelis, an analytical performance modeling tool aimed at reshaping how AI datacenters are planned and optimized.
Imec positioned the platform as a response to pressures facing datacenter designers, as AI workloads expand into the trillions of parameters and energy demands climb. According to the organization, imec.kelis offers a faster and more transparent alternative to conventional simulation tools, which are often slow or limited in scope.
Early adopters have already begun exploring the platform, an early sign of commercial interest.
“Imec.kelis is more than a simulator—it’s a strategic enabler for the next generation of AI infrastructure,” said Axel Nackaerts, system scaling lead.
Imec.kelis provides an end-to-end analytical framework that evaluates performance across compute, communication, and memory subsystems. The tool is optimized for large languagemodel (LLM) training and inference, offering predictions validated on widely used systems such as Nvidia’s A100 and H100 GPUs.
The platform draws heavily on imec’s longstanding expertise in hardware-software co-design, system-level modeling, and semiconductor technology road mapping. Imec said the goal is to give system architects the ability to make better-informed decisions at datacenter scale, where design choices directly impact cost, efficiency, and sustainability.
At the beginning of December 2025, imec continued to demonstrate research leadership at the 71st International Electron Devices Meeting (IEDM), presenting 21 papers spanning advanced logic, memory, quantum computing, imaging, and bioelectronics.
With a high-visibility launch in HPC computing and a deep bench of contributions at IEDM, imec concludes 2025 with strengthened leadership in both advanced semiconductor research and the rapidly expanding AI datacenter ecosystem. The organization is positioning itself as a critical contributor to the technologies that will define next-generation computing infrastructure.
Guillaume de Fondaumiere is the Co-CEO of the Quantic Dream Studio based in France, which developed games such as, “Fahrenheit” (2005), “Heavy Rain” (2010), and in collaboration with Sony Computer Entertainment, the PS3 exclusive title, “Beyond: Two Souls”, starring actors Ellen Page and Willem Dafoe (2013).
Today, on the 15th anniversary of “Heavy Rain,” he finds himself reminiscing: “In the mid-2000s when we started production on “Heavy Rain” I was executive producer on the project. I was also responsible for managing relationships with actors, composers, etc. In the weeks leading up to the launch, we decided with Sony, to send the game to several editorial teams. I remember very clearly sending out those codes, one after another. And a few weeks later we started receiving the first reviews. It was a huge relief to realize that the reviewers had understood what we are trying to do. When we hit after six weeks, one million copies I couldn’t help but shed a tear, telling myself “Phew!”. What I’d tell to myself fifteen years ago in the tough moments, because there are always some during a game’s development, is this: “Don’t worry. It’s going to be okay.”
Guillaume de Fondaumiere was also appointed the Chairman of the European Games Developer Federation. During his position, the French government and the European Union agreed to introduce a 20% tax credit for video games studios. He not only fought for many years to support the gaming industry, but had also lobbied for the games industry to be recognized as an art form.
“To me, all games are a form of cultural expression”, he says. “I see no reason why games should be treated differently than any type of literature or any type of movie. I think that more and more video games are becoming artful, and are becoming a form of art that should be recognized next to the others.” In his opinion, games should be placed among institutional forms of art such as, architecture, sculpture, visual arts, music, literature, theater, cinema art and media arts (television, radio and photography).
Media and internet often sell the information; games trigger the violence, players get addicted to them, and at the end, they are merely entertainment for young and immature minds. The stereotype of thinking associate games with either the shooting or the lighthearted entertainment for children. The reasons for such thinking originate from the early years of the gaming industry, which was actually targeted the children. The first games were very simple, they had boosted the simplest instinctive behavior and the release of adrenaline, which is also referred to as hormone 3F – fear, fight, flight.
But since that time has changed almost everything: games, hardware and the players themselves. Today, the old game enthusiasts had grown up and they still want to play games but they expect deeper, artistic and intellectual entertainment. Under such demanding clients there was a dynamic and multidirectional development of games, and palette of emotions has greatly increased. Today, players can incarnate in any characters, make their own choices, stand for duels with hundreds of players from all over the world. Production studios strive for authenticity and put meticulous attention to details.
Every little part is important, and approaching players to reality. There is also a 3D technology that changed the flat images into three-dimensional images. Today’s game has a story, uses the visual graphics and new, advanced forms of interaction with the player. In addition, there is also increased proliferation of the authors in the games industry, artists express themselves creatively and individually. The impact of games on mass culture is unquestionable and its value is growing at a dynamic pace.
So, is art or not?
A precise, unambiguous, and commonly held definition of art does not exist. However, it is known that art acts through aesthetic, ethical or cultural functions. It affects its audience through watching, listening, creating and reflecting. Without a doubt, the video game industry, which is the fastest growing sector of the modern entertainment industry, is a part of modern culture.
P.S. Roger Ebert, the legendary (Pulitzer Prize) film critic, who for 46 years shaped the tastes of American film audiences, remarked, “as long as there is a great movie unseen or a great book unread, I will continue to be unable to find the time to play video games”. He repeated this statement for eight years and once he hit harder “video games can never be art.”. He died in 2013, with no chance for revision of his assessment.
Medicine—once reactive, treating disease only after symptoms appear—is rapidly evolving into something new. In 2014 American biologist and biotech pioneer Dr. Leroy Hood has offered the clearest vision of tomorrow’s healthcare. He describes the future as 4P Medicine: Predictive, Preventive, Personalized, Participatory. This vision is no longer on the horizon—it has arrived.
This shift, driven by biotechnology and digital innovation, marks one of the greatest transformations in the history of healthcare.
For generations, people have relied on forecasts to guide their daily decisions. When we want to know what the weather will be tomorrow, we open an app on our phone, turn on the radio, or watch the evening news. These predictions help us choose the right clothing, plan a trip, or prepare for a storm. Though convenient, these forecasts are not essential to survival. If we don’t know the weather, life goes on.
But the question “What will my health be like tomorrow?” is very different. Unlike the weather, the answer can determine the course of our life. Will we wake up feeling strong and healthy? Will cold symptoms appear overnight? Or will tomorrow bring a diagnosis that changes everything—a chronic condition, a genetic disorder, or a life-threatening illness? Knowing the future of our health is profoundly important, yet for most of human history, this knowledge has been out of reach.
Traditional medicine waits. It waits for pain, for symptoms, for problems that must be solved after they occur. For centuries this was the only option, because doctors lacked tools to understand what was happening inside the human body before illness appeared.
But advances in biotechnology, genetics, and data analytics are rewriting the rules. Modern medicine is beginning to resemble weather forecasting: predictive models built from enormous streams of data can now indicate our health risks long before we feel anything.
The science behind this new capability builds on several breakthroughs:
Genomics, which maps our genetic predispositions
Wearable sensors, which collect real-time data about physiology
Artificial intelligence, which identifies patterns invisible to humans
Behavioral tracking, which captures environmental and lifestyle influences
Together, these tools allow physicians to anticipate illness rather than simply react to it.
Millions of people now wear devices that continuously track: heart rate, oxygen level, activity and movement, sleep stages, blood pressure, blood glucose levels or stress signals. These sensors turn our bodies into sources of data, providing information that once required clinical visits. When combined, these data streams create a high-resolution portrait of our health.
The smartphone has quietly become the central device in digital medicine. It stores our medical data, tracks behavior, connects to wearable devices, and hosts apps that analyze symptoms, drug interactions, and lifestyle patterns. For the first time in history, billions of people carry clinical-quality sensors in their pockets.
The human body produces enormous amounts of information each second. Until recently, we lacked the tools to interpret it. AI changes everything. Machine learning models can detect: early sign of heart disease before symptoms occur, cancer signatures in bloodwork, anomalies in breathing and sleeping. AI operates like a constant medical companion, analyzing data streams and alerting us to risks long before a crisis emerges.
The discovery of DNA’s structure in the 1950s was one of the most significant moments in science. But only today—thanks to advances in sequencing—are we fully unlocking its potential. This revolution means individuals can now: understand their genetic predisposition to hundreds of conditions, tailor diet, exercise, and lifestyle to their genetic profile, detect carriers of hereditary diseases within families. Genomics is no longer a laboratory dream—it is becoming part of everyday healthcare.
Artificial intelligence is impacting the music industry at a rapid pace, offering tools for impromptu creation, production, and even performance. Along with text, images, and videos, generative AI can also produce music, assist with songwriting and production, and even replicate voices in a matter of seconds. Deep learning is based through its training data, which through its underlying patterns and structures is used to produce new data based on the input, which often comes in the form of natural language prompts.
There are numerous websites that use this technique, such as Suni, AIVA, Udio just to name a few, that can generate a complete song with music and lyrics in a certain style, mood, instrumentation, genre, and vocal style with just a brief description and a click of a button. These prompts can be entered directly or created using external tools like ChatGPT, which generates the lyrics.
For example, the user can enter into the Suni song description field “a song in the style of classical music about a ballet dancer struggling to find success in her career”. In just seconds with a click on the “create” button, the user will be able to hear a complete song that sounds like it was written by a semi-professional songwriter, with fairly decent lyrics.
Now, anyone can create music…well at least generate it.
Will the listening music public start listening to music produced entirely by A.I. instead of the real music we know and love?
The answer is many of them already are without really knowing it.
A.I.’s “The Velvet Sundown”
For example, last June, “The Velvet Sundown” (named after “The Velvet Underground”) came out of nowhere and released its first albums on Amazon Music, Apple Music, Spotify as well as other music streaming services: “Floating on Echoes” on June 5, “Dust and Silence” on June 20, and then another on July 14th called “Paper Sun Rebellion”. At their peak, they had well over 900,000 monthly listeners on the streaming platform with their opening track “Dust on the Wind”, (not to be confused with the iconic Kansas song) played over 2.7 million times.
However, there were soon allegations on the bands social media pages that the band was A.I. generated. There was no evidence that this band ever existed. There were no tours, interviews, group websites or any clues whatsoever online. Even many listeners commented that The Velvet Sundown’s music was “soulless” and was missing the “human element”.
The “band” denied all allegations on its X account, claiming it was “absolutely crazy that so-called ‘journalists’ keep pushing the lazy, baseless theory that the Velvet Sundown is ‘AI-generated’ with zero evidence.… This is not a joke. This is our music, written in long, sweaty nights in a cramped bungalow in California with real instruments, real minds and real soul.”
Just a week later, the apparent hoaxer, using the name Andrew Frelon, admitted that he impersonated the band on X and falsely claimed to be a spokesperson for the band in interactions with the media, including a phone interview with Rolling Stone magazine. Frelon finally admitted that the band was 100% A.I. generated using the Suni platform for all the “band”.
“It’s marketing. It’s trolling. People before, they didn’t care about what we did, and now suddenly, we’re talking to Rolling Stone, so it’s like, ‘Is that wrong?’” Frelon questioned.
As with the Spotify subscriber numbers since the “bands” breaking news, over 500,000 subscribers removed their names from the “bands” playlists, a drop of 55% from its peak, as it continues to drop quickly on a daily basis.
The bands Spotify bio eventually changed their description:
“All characters, stories, music, voices and lyrics are original creations generated with the assistance of artificial intelligence tools employed as creative instruments. Any resemblance to actual places, events or persons – living or deceased – is purely coincidental and unintentional. Not quite human. Not quite machine. The Velvet Sundown lives somewhere in between.”
The real issue is its sudden emergence of its popularity and a growing concern about the future of art, culture and authenticity in the era of advanced generative artificial intelligence. It’s both astounding and appalling that music from A.I. can amass and defraud so many listeners in a relatively short amount of time.
“Personally, I’m interested in art hoaxes,” Frelon continues. “The Leeds 13, a group of art students in the U.K., made, like, fake photos of themselves spending scholarship money at a beach or something like that, and it became a huge scandal. I think that stuff’s really interesting.… We live in a world now where things that are fake have sometimes even more impact than things that are real. And that’s messed up, but that’s the reality that we face now. So it’s like, ‘Should we ignore that reality? Should we ignore these things that kind of exist on a continuum of real versus fake or kind of a blend between the two? Or should we dive into it and just let it be the emerging native language of the internet?’”
In another similar hoax “project” from decades ago, one can’t forget the infamous story of the pop group Milli Vanilli and it’s producer Frank Farian, who may have pulled the biggest hoax in popular music history: selling over 7 million albums and 30 million singles, and winning a Grammy for “Best New Artist” by deceiving the public with a pair of lip-synching performance artists who did not sing one note on their records.
Even with the regret and humiliation that Milli Vanilli producer Frank Farian went through, at least their end product was “real music” that used professional musicians and was produced in a recording studio. That takes real talent.
In a notable moment for the music industry, an A.I.-assisted Beatles song, “Now and Then,” won the Grammy for Best Rock Performance in 2025. It was the first time an AI-assisted song received one.I-assisted song received one.
You can credit director Peter Jackson and his production team who worked on the 2021 “The Beatles – Get Back” documentary. They developed an A.I. tool (MAL) for the film and discovered that they could use it to extract John Lennon’s voice from a demo cassette tape recorded in 1974 that originally had Lennon’s piano and vocal on it. They were able to isolate the tracks mixed into a 2 track master and later combined the original 1995 guitar tracks that George Harrison recorded from their “Now and Then” recording session along with McCartney and Starr, who decided to re-record their tracks in 2023 for a true authentic Beatles recording.
Currently, unless you have access to Peter Jacksons MAL A.I. tool, it appears the only way to tell if the music is A.I. generated is if you have software such as Apple’s Logic Pro track splitter and finding “artifacts” from the inputted music files, as music producer Rick Beato calls it.
Also, the music streaming app Deezer, also uses its own tool to identify AI-generated content and declared that 100% of The Velvet Sundown’s tracks were created using A.I. Deezer labels that content on its site, ensuring that AI-generated music does not appear on its recommended playlists and that royalties are maximized for human artists.
Unlike generative A.I., there is nothing fake with the Fab Four latest song, “Now and Then”… it’s just real music with real musicians with a little help from A.I. and their friends; producers Peter Jackson, Giles Martin and George Martin with all of the original Beatles back together again.
“Imagine” that.
Originally published on https://mlsentertainment.com/2025/08/31/milli-vanilli-or-the-velvet-sundown-discerning-real-music-in-the-a-i-era/
Over the past decade, data centers have served as the digital backbone of modern life—warehouses of servers designed to store information, host applications, and deliver content across the internet. But the rise of large-scale artificial intelligence has fundamentally changed what these facilities need to do. Traditional data centers are evolving into AI factories highly specialized, compute-intensive environments designed to train and run AI models at unprecedented scale. This transformation is reshaping architecture, operations, energy consumption, and economics across the tech ecosystem.
NVIDIA held its main GTC (GPU Technology Conference) in San Jose, California, from March 17-21, 2025, focusing heavily on transforming data centers into AI factories with Blackwell Ultra and Reuben architectures, plus AI-powered robotics. Yes, the data centers are no longer in fashion. The AI factories is the word that is describing the transformation what has been happening in technology world.
GTC 2025 solidified NVIDIA’s vision for an AI-driven future, emphasizing massive AI factories, a reinvented computing stack, and the practical application of AI across all industries – from healthcare, life science to manufacture robotics, autonomous vehicles, computer graphics, even video games. Jensen Huang found himself reminiscing on Video games that started Nvidia company in 1983 running the first application and the journey where Nvidia is now.
Key NVIDIA GTC 2025 Themes & Announcements:
AI Factories & Infrastructure: Shift to full-stack accelerated computing, with Blackwell Ultra boosting reasoning workloads and Reuben architecture offering massive performance gains (900x scale-up flops).
Software & Platforms: Introduction of Nvidia Dynamo, an OS for AI factories, and platforms for connecting millions of GPUs.
Physical AI & Robotics: Reality of AI in robotics, logistics, and manufacturing, with demos of self-driving cars and digital humans.
Industry Focus: Deep dives into healthcare (drug discovery), telecommunications (AI-RAN), and public sector AI.
Geopolitics & Sovereign AI: Initiatives for nations to control their own AI infrastructure.
