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UserTesting buys User Interviews, eyes high-end human feedback loops

UserTesting buys User Interviews, eyes high-end human feedback loops

UserTesting, which provides customer experience insights, said it has acquired User Interviews, a platform for recruiting people for user and market research as well as AI training.

The move brings together two complementary companies that have multiple joint customers. UserTesting and User Interviews appeal to designers, researchers, product managers and marketers.

Terms of the deal weren't disclosed.

UserTesting provides an insights platform and a global general population network. User Interviews has a premium participant marketplace. UserTesting CEO Eric Johnson said the companies together will make it easier to recruit the right participants for feedback across multiple industries and research use cases. The combined offering will also be able to ground AI deployments, products, marketing and customer experience efforts with real human insights.

"By bringing UserTesting and User Interviews together, we’re creating the fastest and most reliable way for teams to understand their customers and make better, smarter decisions with confidence," said Johnson.

User Interviews CEO Basel Fakhoury said combining the company's panel capabilities with UserTesting's platform will be a win for enterprises and joint customers looking for customer insights.

The combined company reckons that it will have more reach, precise targeting and matching, proprietary fraud detection, scale and enterprise-grade trust.

Constellation Insights caught up with Johnson and Fakhoury to talk shop. Here are the takeaways.

The rationale behind the deal. Johnson said he has been meeting with customers since taking over as CEO in September 2024. The one feedback that kept coming back was to find the right participants to deliver the right feedback. "This acquisition is incredibly strategic. Our customers said the one thing they need is they need the right participants to get the feedback right," said Johnson. "They need the right human beings. In many cases, the customer actually wants a B2B professional. It could be a doctor, lawyer or developer. It's a really bespoke person and those people are not the easiest to find."

User Interviews had built a platform that can deliver those bespoke people. "What we're doing is we're bringing together the best overall customer insights company and general population panel with the best company on Earth to go out and find these hard to find people," said Johnson.

Johnson and Fakhoury began talking roughly a year ago about partnerships. Over time it became clear that customers and employees thought a merger made sense.

Finding the right panel participants. Fakhoury said User Interviews has built a platform that has a broad number of people with specific characteristics. To reach those people, email doesn't work. "SMB owners or doctors are generally not in these networks. If you get emailed to participate in a study, and then you don't get selected for that study, you're not going to apply to the next one. It's just not worth it," said Fakhoury. "We've invested in the matching algorithms so that when someone launches a project we send it to the people most likely to qualify. The participants end up trusting us. That matching technology is really our differentiation. We think about the participant experience. It's a virtuous cycle."

"We built this network and these flywheels that I think are really hard to reproduce, and that's allowed us to be very efficient at what we've done," added Fakhoury.

Feedback fatigue and delivering value. Johnson and Fakhoury both noted that the survey and feedback fatigue is real. That's why finding the right people, paying them and finding the right human fit matters so much. "I didn't come from customer insights before, but entering this market, what I realized is the value of this. This is actually really hard but it is the most important part to getting rich feedback, because if you don't have the right people, no matter how great your feedback mechanisms are, no matter how great your AI is, you have nothing. And so that's why, as a company, our business strategy is to do this part exceptionally well," said Johnson.

Johnson added that the human feedback loop is critical to AI. "You start with the quality of the data you put into it. Because we have the best ability to talk to the right humans, and we have the largest volume of customers generating this kinds of feedback, we are uniquely positioned to provide the best AI, whether it's AI summarization, whether synthetic feedback, or whether it's AI simulations," said Johnson.

Constellation Research’s take

Constellation Research analyst Liz Miller assessed the deal.

“On the surface, this is a masterclass in acquisitions: an emerging player with great technology, great product and great customers gets picked up by a bigger player that can immediately accelerate technology roadmaps thanks to the great technology. The combined company can immediately offer mutual customers greater flexibility and opportunity while simultaneously taking advantage of new customer opportunities. The fit feels obvious here.

Below the surface is where this acquisition gets interesting because as many have pointed out, we are in this age of AI where brands can and should access intelligence about the market, product, or customer in a moment. The problem remains that these insights systems are already running out of the data needed to continue to make contextual decisions well. We need new and more valued sources of insight. And we can’t wait for traditional focus groups or even modern paths to synthetic data to get the job done. We want and need humans in THIS loop. We can analyze all the data in the world with AI, but human-centric panels and opportunities for interview-based insights takes customer-driven decisioning to a whole new level. That’s what UserTesting + User Interviews can offer: accelerated access to humans to ensure that human-in-the-loop decisioning isn’t just possible, it's easy. “

Data to Decisions Next-Generation Customer Experience Innovation & Product-led Growth Chief Customer Officer Chief Executive Officer Chief Information Officer Chief Marketing Officer Chief Product Officer

Epicor set final on-prem release dates for Kinetic, Prophet 21 and BisTrack

Epicor set final on-prem release dates for Kinetic, Prophet 21 and BisTrack

Epicor outlined its schedule of final releases for on-premise versions of Epicor Kinetic, Epicor Prophet 21 and Epicor BisTrack. Future versions of three enterprise resource planning (ERP) offerings will move to Epicor Cloud.

The company offers a set of ERP systems along with supply chain management, retail management, financial management, manufacturing execution and data management and analytics. Epicor has 23,000 customers, 4,600 employees and 2.3 million daily users.

According to Epicor, moving customers to cloud versions will deliver innovation, business agility and AI tools faster.

Vaibhav Vohra, President and Chief Product & Technology Officer at Epicor, said the final on-premise releases represent a milestone for the company and represent an inflection point in delivering cognitive ERP. "We will closely work with our customers every step of the way via Epicor Support, through our AI-powered Ascend with Epicor migration program, and with our industry-first innovations such as conversational ERP," said Vohra.

Epicor said that customers using on-premises versions of Kinetic, Prophet 21, and BisTrack will continue to receive support. After the final on-prem releases support will transition into Active Support followed by Sustaining Support. Epicor and its partners offer a series of migration tools and programs.

Here's a look at the timelines

Kinetic

  • Final on-premises release: 2028.1 tentatively scheduled January 2028
  • Active Support for release 2028.1 through December 31, 2029
  • Sustaining Support begins January 1, 2030

Prophet 21

  • Final on-premises release: 2028.1 tentatively scheduled May 2028
  • Active Support for release 2028.1 through June 30, 2029
  • Sustaining Support begins July 1, 2029

BisTrack

  • Final on-premises BisTrack Web Browser & API release 2028.1 tentatively scheduled July 2028
  • Active Support for on-premises BisTrack Web Browser & API release 2028.1 through June 30, 2029
  • Sustaining Support for on-premises BisTrack Web Browser & API release 2028.1 begins July 1, 2029
  • BisTrack Desktop final release 2026.2 tentatively scheduled December 2026
  • Active Support for BisTrack Desktop through December 31, 2028
  • Sustaining Support for BisTrack Desktop begins January 1, 2029
  • BisTrack UK 3.9 (2017): Active Support through December 31, 2026; Sustaining Support begins January 1, 2027

 

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AMD previews Instinct MI500 GPUs, physical AI, Helios integrated racks

AMD previews Instinct MI500 GPUs, physical AI, Helios integrated racks

AMD teased its Instinct MI500 GPUs, which will launch in 2027, gave an early look of its Helios rack scale platform and touted the need for yotta-scale infrastructure.

Yotta-scale represents an expansion from today's 100 zettaflops of global compute capacity to more than 10 yottaflops. Think 24 zeroes and 10,000 more compute available than 2022.

AMD CEO Lisa Su during her CES 2026 keynote aimed to position the company as an effective counterweight to Nvidia with reach into AI infrastructure, physical AI and robotics and edge use cases including AI PCs. Su featured a host of customers including OpenAI, Blue Origin, Generative Bionics and AstraZeneca to name a few.

The news that got the most attention was the Instinct MI500 GPUs as AMD needs to keep up with Nvidia's annual cadence. The Instinct MI500 GPUs provide 1000x more AI performance than the MI300x GPUs built in 2023. AMD's Instinct MI500 GPUs are built on AMD's next-gen CDNA 6 architecture and 2nm process technology.

"The MI400 series was a major inflection point in terms of delivering leadership training across all workloads, inference, scientific computing," said Su. "But we are not stopping there. Development of our next-gen MI500 series is already well underway."

AMD also positioned itself as a full-stack AI provider with the early look of Helios, which includes 3 exaflops in a single rack. Helios, the product of the ZT Systems acquisition, features MD Instinct MI455X accelerators, AMD EPYC "Venice" CPUs and AMD Pensando "Vulcano" NICs for scale-out networking. The processors are integrated with AMD's open ROCm software.

The company highlighted AMD Instinct MI440X GPU, which is designed for on-premises enterprise AI deployments used for training, fine-tuning and inference in an eight-GPU system.

Su's keynote at CES 2026 did what it had to do--position AMD as a viable alternative to Nvidia's dominance. Here's a look at the key news from AMD at CES 2026.

AMD outlined Ryzen AI Embedded processors, a portfolio of embedded x86 processors for AI edge applications. The portfolio, including AMD's new P100 and X100 Series processors, is designed for everything from automotive cockpits, healthcare and physical AI and robots. Su aimed to position AMD well for physical AI and robotics, which are the main theme at CES 2026. She said:

"At AMD, we spent more than two decades building the foundation of physical AI today. We're doing it together with a broad ecosystem of partners. Physical AI is one of the toughest challenges in technology. It requires building machines that seamlessly integrate multiple types of processing to understand their environment, make real time decisions and take precise action without any human input, and all of this is happening with no margin for error. Delivering that kind of intelligence takes a full stack approach."

The company expanded its AI PC portfolio including AMD Ryzen AI 400 Series and Ryzen AI PRO 400 Series processors.

Ryzen AI Max+ 392 and Ryzen AI Max+ 388 are processors designed for on-device AI compute with the ability to support models up to 128-billion parameters and 128GB unified memory.

AMD also launched the Ryzen AI Halo Developer Platform, available in the second quarter, to bring AI development to a desktop PC. The developer platform is AMD's first branded effort for AI developers.

AMD announced AMD ROCm 7.2 software for Windows and Linux.

Constellation Research's take

R "Ray" Wang, founder and CEO of Constellation Research, speaking to Bloomberg outlined significance of physical AI as the next trillion-dollar market opportunity. He said Nvidia's early release of Vera Rubin chips is a game-changer that accelerates timelines. 

Wang views Nvidia as more than a GPU player, but a full-stack ecosystem vendor that includes chips, software, and device partnerships. 

When comparing rivals:

  • Nvidia is currently dominating the GPU market.
  • AMD is positioned as a competitor launching new GPUs and looking to provide more efficient chips with wider availability. Wang expects AMD to showcase partnerships in the data center space as an alternative to Nvidia.
  • Intel is seen as a more state-sponsored approach, focusing on manufacturing in the US.

Data to Decisions Tech Optimization AMD Chief Information Officer

Monday's Musings: Davos 2026 - In A Spirt of Dialogue, Conversation Starters For Debate (Part 1)

Monday's Musings: Davos 2026 - In A Spirt of Dialogue, Conversation Starters For Debate (Part 1)

Media Name: @rwang0 @davos @wef #WEF2026 #Davos2026 #WEF26 #Davos26 Davos_Congress_Centre.jpg
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World Economic Forum's 2026 Theme Centers Around "A Spirit of Dialogue"

Another year, another Davos.  With 3000 official and 5000 unofficial attendees at UnDavos and a host of amazing side events, the beginning of the year marks a rite of passage for the C-Suite.  While convening high above the Swiss Alps, these global leaders will "talk" about the state of world affairs and economy, Many skeptics wonder if real dialogue will be had. 

Good news -  this year's World Economic Forum's 2026 Theme Centers Around "A Spirit of Dialogue".  Per theme, official discussions are centered around five key global challenges:

  1. Cooperation in a contested world;
  2. Unlocking new sources of growth;
  3. Investing in people;
  4. Deploying innovation responsibly; and
  5. Building prosperity within planetary boundaries.

Taking a Constellation Research futurist point of view (POV), let's apply a PESTEL framework to these themes and provide some conversation starters for provocative points of view and the authentic dialogue much needed at Davos.  We'll start with the first three (i.e. PES) and continue (TEL) in Part 2.

Politics

1. Can we fight the scourge of socialism and prove that capitalism is still the best system?

A recent survey by the Cato Institute and YouGov paints a troubling picture: 62 percent of Americans aged 18–29 say they hold a “favorable view” of socialism, and 34 percent say the same of communism. This is shocking given that communism is responsible for 100 million deaths worldwide and is rooted in socialism, the same philosophy that spawned both Mussolini’s fascism and Hitler’s National Socialism. To favor socialism is to flirt with tyranny.

The poll did not define “socialism.” So, it’s unclear whether the respondents view it in the historical way, where the state owns the means of production, or if they see socialism as a modern-day “mixed economy” with cradle-to-grave welfare, price controls, and “fairness” enforced by the state.

What can be done to educate younger generations on the dangers of a mixed economy which Ayn Rand and Ludwig Von Mises warned future generations about?

2. In 2026 and beyond, will countries and companies have to choose a side between China vs US?

As the United States and China intensify their competition on the political, economic, technology, and military scale it seems inevitable that the deepening rivalry creates a mutually exclusive relationship when strategic alignment with one power will come at the expense of deeper ties with the other.  With the impact of Tariffs and the US "Donroe" doctrine in place, nation states must factor in the ripple effects in geopolitics.

While many nations and companies prefer not to choose, what can be done to navigate between security ties and economic relationships?  Is strategic autonomy even an option with countries trying to reap benefits from both sides without any consequences from either great power notes a (Chatham House Sept 2025) article?

3. When will dollar dominance wane and will BRICS replace "king" dollar?

With over 90% of foreign exchange transactions using the dollar, the dollar remains king in international trade and is a core reserve currency.  The dollars liquidity, convertibility, and stability has led to its dominance in global reserves.  However the share has been falling with 71% in 2001 to about 58% in the past few years.  BRICS have increased bilateral trade in local currencies with Russia and China using the yuan and India buying oil in rupees to bypass the US Dollar.  

 

The IMF predicts that by 2028 the BRICS+ block will represent 38% of global GDP.  In addition, India and China have been adding to their gold reserves as a way to diversify from the US Dollar.  What factors will lead to BRICS dominance and dollar decline or will the dollar remain "King"?

Economics

1. What will be the economic costs and benefits in the Battle for AI dominance?

Constellation predicts over $6 trillion will be invested in AI Infrastructure by 2030 with annual budgets exceeding $1.5 trillion.  The massive capital expenditures for chips, data centers, energy grids, water resources, and additional green house gas emissions will place a massive economic cost. The likely winner-takes-all scenarios for AI dominance favors tech giants with deep pockets and sovereign nations such as the Kingdom of Saudi Arabia (KSA). In KSA's case they will enter a metamorphical transition from energy dominance to compute dominance.  With a widening AI gap between resource heavy nations and resource constrained nations, will the benefits outstrip the costs?  Should one entity achieve artificial general intelligence (AGI) or Artificial SuperIntelligence (ASI) before another, what will the resulting economic impact mean for business models?

2. Can the West compete with China's energy advantage? 

The average price of electricity is $0.25 kWh for Europe, $0.15 kWh for the US, and $.08 kWh for China.  With a 2X to 3X advantage, China's rapidly moving to $0.04 kWh given the massive state backed investments in energy infrastructure from coal fired plants, to renewable energy.  China added almost 400 GW of Solar and Wind in 2025, 10 new nuclear reactors with 60GW, and 80 GW of coal fired electric capacity.  Furthermore, advancements in Ultra-High Voltage (UHV) technology (1000kV AC and ± 800kV DC) allows for minimal transmission losses of 1.5-3% per thousand kilometers.  Given the faux pax in green initiatives of the West which have driven up costs, created inflation, and left countries helpless to economically compete, what will the West do to catch up?

3. Will today's banking system be relegated to the past with the growing black market trade on chain?

Many predict that global trade will leave publicly transparent financial systems for shadow markets built on the blockchain.  Constellation sees the user facing layer of the crypto economy growing with the rise of stablecoins and tokenized assets.  With over $250 billion in nmarket cap for Us dollar-pegged coins, the future is pretty clear.  IN 2024, these US dollar-pegged coins moed $27.6 trillion in volume, which is more than Mastercard and Visa combined. What is the future of a value exchange and trading system no longer controlled and regulated by state actors and international regulators?

Societal

1. What will humanity's purpose be in an AI Age?

How will humanity's purpose evolve as AI advances? With AI and automation promising ambient to automated experiences, the nature of work the meaning of human existence is at a juxtaposition between a world pre AI and post AI.  Will AI improve the human condition or will it worsen the human condition?  What will AI advance that humans cannot and what will humans advance that AI can not? 

Note: Catch the session Tuesday January 20th at 11:30 am to 1:30 pm Cognizant House Promenade 68. Register here.

2. How will population dynamics impact the future social order and create demographic divides?
 
The United Nations (UN) projects a peak global population around 10.3 billion in the 2080s, followed by a slight dip to 10.2 billion by 2100. In almost every projection, India will become the world's most populous country peaking in 2061 and then gradully declining while China's population will fall sharply by 2100.  Africa will drive global growth with countries such as DRC, Ethiopia, Nigeria, and Tanzania contributing to sharp rises in population  The United States is expected to remain flat to very slow growth.  By the mid 2030s, the number of 80+ will outnumber the number of infants.  IN 2080, the number of people over the age of 65 will outnumber the children under 18. 
 
Constellation expects gaps in social, economic, and population health outcomes between nations due to population dynamics such as varying birth/death rates, fertility trends, age structures (young versus old).  As countries move from high birth rates to low ones, societal structures, social security systems, labor, and healthcare will face new constraints.  For example, birth rates are 1.6 in Europe and North America while Sub-Saharan Africa has high birth rates in the 4.3 to 4.5. will require governments to invest more in healthcare, education, and housing infrastructure.
 
Will aging societies make the shift in resource allocation from housing, education and childcare to more healthcare, technology automation, and aging population infrastructure?  Will rapidly growing younger populations be able to invest for the future? What will immigration policies look like in this new world order?  Can countries with aging populations use humaniod robots to replace their labor force in time?
 
3. Will higher education continue as we know it?
Higher education faces a confluence of demise from declining undergraduate enrollment, shrinking student populations, rising costs, lack of public trust, and questions of value and ROI.  The bifurcation between top-tier colleges and less elective colleges without a path to jobs will continue to widen.  The demographic cliff is the most significant factor as credential inflation and skill gaps increase as rising tuition and a weakened job market shifts the future of episodical education to a future of life long learning. 
 
Given the trillions of dollars of future investment in data centers, precision manufacturing, energy infrastructure, and construction, many believe skilled trades will outperform the investment in higher education,.  With faster earnings, lower debt, greater job security, and wealth creation, demand for vocational training may create a fundamental shift in learning for the next few decades.  Will higher education be the riskier bet in the future and skilled trades replace the "traditional" path to future financial and career success?
 

The Bottom Line: Are You Really Ready For Some Honest and Authentic Dialogue?

The public Davos panels and keynotes have often been an overscripted, highly sanitized, corporate communications by committee, public relations driven event.  Meanwhile, the private meals and smaller group events have been the source of insightful conversations and relationship building.  Maybe in 2026, we can flip th script and just cut to the chase and have real dialogue.  Will you be that force for change?

Your POV

It's that time of year.  Will the elites actually have something useful to say this year or will it be another year of muckety mucks pontificating about useless issues?  Will America 250 change the dialog?

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Nvidia touts Rubin platform production, hardware advances

Nvidia touts Rubin platform production, hardware advances

Nvidia said its Rubin platform is in full production as it rolled out a series of hardware updates at CEO Jensen Huang's CES 2026 keynote.

Huang said the Rubin platform will offer an integrated hardware and software stack that will provide a 10x reduction in inference token costs and a 4x reduction in the number of GPUs needed to train foundational models relative to Nvidia's Blackwell platform.

The company also noted that Microsoft's next-gen Fairwater AI factories will feature Nvidia Vera Rubin NVL72 rack systems with CoreWeave being among the first to offer the latest platform.

Huang's keynote walked through a lot of backstories for Vera Rubin and its various networking and storage components. "Vera and Rubin are co designed from the start to bi directionally and coherently share data faster and with lower latency," said Huang.

Here's what you need to know about Nvidia's hardware announcements:

  • Nvidia's Rubin platform uses "extreme codesign" across six chips including Vera CPU, Rubin GPU, NVLink 6 Switch, ConnectX-9 SuperNIC, BlueField-4 DPU and Spectrum-6 Ethernet Switch.
  • Adoption of the Rubin platform is broad with most AI labs and cloud providers on board.
  • Huang outlined Nvidia BlueField 4, which is behind the Nvidia Inference Context Memory Storage Platform, an AI-native storage system for inference.
  • BlueField 4 is designed for long-context processing agentic AI systems.

Data to Decisions nvidia Chief Information Officer

Nvidia highlights its robotics momentum as Qualcomm makes its platform case

Nvidia highlights its robotics momentum as Qualcomm makes its platform case

Nvidia released new Cosmos and GR00T open models for both learnings and reasoning and a new framework for robotic training workflow. The company also outlined a strong ecosystem for autonomous machines and the availability of the Blackwell Jetson T4000 module.

At CES 2026, robotics was the big theme with a lot of hype focused on humanoid robots. Constellation Research analyst Esteban Kolsky argued in his newsletter that the focus on humanoid robots is a mistake. "Humanoid robots are the worst possible path we can take. Despite Hollywood’s love of anthropomorphized animatronics, there are many deficiencies in human-shaped and look-alike robots," said Kolsky in The Board: Distillation Aftershots.

Nevertheless, the combination of robotics and AI will be powerful and Nvidia and challengers such as Qualcomm all want to be dominant platforms. Robotics company Boston Dynamics, owned by Hyundai, outlined a collaboration with Google on models.

During his CES 2026 keynote, Nvidia CEO Jensen Huang couldn't resist bringing out a cast of robots. The not so subtle message: Nvidia's platform powers robots from Boston Dynamics, Caterpillar, Franka Robots, Humanoid, LG Electronics and NEURA Robotics. Nvidia is also integrating its Isaac models and libraries with Hugging Face and LeRobot.

"Nvidia’s full stack of Jetson robotics processors, CUDA, Omniverse and open physical AI models empowers our global ecosystem of partners to transform industries with AI-driven robotics," said Huang.

Nvidia launched the following open robotics models.

  • Cosmos Transfer 2.5 and Cosmos Predict 2.5, two world models that can be customized.
  • Cosmos Reason 2, a reasoning vision language model.
  • Isaac GR00T N1.6, an open reasoning vision language action (VLA) model for humanoid robots.

Huang pointed out robotics use cases for healthcare, manufacturing and construction via a collaboration with Caterpillar.

Nvidia is clearly going for scale. The company said its new Jetson T4000 module brings Blackwell to robots and can bring costs to $1,999 at a 1,000 unit volume. Huang highlighted a partnership with Siemens for physical AI and robotics.

"As the global labor shortage worsens. We need automation powered by physical AI and robotics more than ever," said Huang.

Qualcomm's robotics plan

Qualcomm at CES rollout out its robotics architecture that combines hardware, software and AI. Qualcomm also outlined its next-gen robotics processor for industrial robots as well as humanoids with its Qualcomm Dragonwing IQ10 Series.

In a nutshell, Qualcomm wants to be the energy efficient brain in robots that are mobile and autonomous. Qualcomm is also building a robotics ecosystem with partnerships with Figure, which makes humanoid robots, and other players including Advantech, APLUX, AutoCore, Booster, Figure, Kuka Robotics, Robotec.ai, and VinMotion.

Key items include:

The robotics play is part of the broader IoT plan for Qualcomm, which has built its broader IoT platform via the acquisitions of Augentix, Arduino, Edge Impulse, Focus.AI and Foundries.io. At CES, Qualcomm outlined its Q7790 and Q8750 processors designed to power on-device AI across multiple devices. Here's the stack.

 

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A look at how Mercedes Benz, Nvidia collaborated on autonomous vehicles

A look at how Mercedes Benz, Nvidia collaborated on autonomous vehicles

Nvidia outlined its Alpamayo open AI models and datasets to bring reasoning to autonomous vehicles. At CES 2026, Nvidia CEO Jensen Huang said Mercedes Benz with Alpamayo will hit the road in the first quarter.

Huang said Alpamayo and its collaboration with Mercedes Benz is its first full-stack effort for autonomous vehicles (AVs). The approach with Alpamayo revolves around reasoning-based vision language action (VLA) models that bring human thinking to autonomous vehicle designs.

"Our vision is that someday, every single car, every single truck, will be autonomous," said Huang.

It's a vision shared by Ola Kallenius, CEO of Mercedes-Benz Group AG, spoke on a panel about the company's AV efforts with Nvidia.

"I had a chance with the combined Mercedes and Nvidia team to drive it through San Francisco and down into Silicon Valley is point to point navigation," said Kallenius, who noted the AV was operated by "a very sophisticated level two system.

Kallenius noted that the system with Nvidia is more like level 2 plus. "It feels that the car is on rails you're just driving, and it does everything. I drove uninterrupted for more than an hour through pretty heavy traffic," he said.

The general idea behind Alpamayo is to create a model and system that can handle novel or rare driving scenarios. Huang said Nvidia will support the models and AV systems on a long-term basis. For Nvidia, the AV effort is a bridge to robotics.

Nvidia released:

  • Alpamayo 1, a chain-of-thought VLA model for AV researchers. The model is on Hugging Face and has a 10-billion parameter architecture. The model uses video input to reason and show its logic.
  • AlpaSim, an open source end-to-end simulation framework.
  • Physical AI open datasets with more than 1,700 hours of driving data.

Nvidia said Lucid, JLR, Uber and Berkeley DeepDrive were showing interest in Alpamayo. Huang added that Nvidia's full autonomous driving stack includes Alpamayo, a policy and safety evaluator, classical AV tools and Halos Safety OS.

According to Huang, the effort with Mercedes Benz took several thousand people and at least five years of work. "This entire stack is vertically integrated. Of course, in the case of Mercedes Benz, we built the entire stack together. We're going to deploy the carbon, operate the stack, and maintain the stack for as long as we shall live," said Huang.

Kallenius said the Nvidia collaboration with Mercedes Benz revolves around safety.

"If you're moving an object that weighs 4,000 pounds, and it's moving at 50 miles an hour, sorry is not going to cut it. There needs to be a higher level of certainty and safety. You don't have to rush into the market. You don't have to be the first but you got to make sure that what you do is robust," said Kallenius.

 

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Samsung, HSB eye bridge between appliances, AI and your home insurance

Samsung, HSB eye bridge between appliances, AI and your home insurance

Samsung and Munich Re's Hartford Steam Boiler (HSB) unit, which offers insurance for equipment breakdown, are planning to leverage IoT sensors, AI and smart appliances to spin up personalized home insurance. Welcome to the 2026 monetization of AI use cases.

The model was outlined as part of Samsung's First Look presentation at CES 2026, which included a plan that revolves around connecting and embedding on-device and cloud AI throughout its appliance lineup with a unified OneUI experience. More thoughts on that later including my working theory that consumers will pay premiums to have dumb appliances that just do what they're supposed to and are reliable.

But the HSB-Samsung partnership is worth noting because it's a financial incentive that may prod consumers to bring more AI into their everyday experiences. Now you may not need or want Bixby as an AI experience or Google Gemini powered AI vision to examine the food in your fridge or AI recipe recommendations, but with some financial incentives you might. The catch: HSB insurance appears to mean that everything in your house needs to be connected via Samsung's SmartThings.

Based on Samsung's presentation, even your steam wrinkle iron needs a Qualcomm Dragonwing processor.

However, the HSB partnership with Samsung is going to expand beyond a pilot in the US to more states. HSB President and CEO Greg M. Barats said smart appliances connected to SmartThings can lower risk and premiums.

"Using information from these connected appliances, we assess the characteristics of your smart home and enable a truly personalized offer, knowing that you have appliances smart enough to alert you a small leak before it floods your kitchen, we can help you avoid costly, time consuming claims."

In a nutshell, HSB and Samsung want to apply the industrial AI preventative maintenance use case to your home.

HSB in 2025 launched its Meshify Defender Slim sensor, powered by Amazon Sidewalk, to monitor buildings and homes for water leaks and frozen pipes. HSB and Flume also offer water leak protection.

This pilot with HSB and Samsung is worth watching since it highlights how AI may be monetized going forward. Use of AI and models in insurance is also notable. 

Thoughts on Samsung's AI strategy

Samsung's First Look included a 130-inch TV, an AI-driven Family Hub refrigerator, a Bespoke AI Laundry Combo that eliminates the need to transfer loads of laundry and a Bespoke AI Jet Bot Steamer.

TM Roh, CEO and Head of Samsung’s Device eXperience (DX) Division, said:

"Our mission is clear to be your companion to AI living, and our strategy is simple. We will harness the full scale of Samsung to create technologies and experiences that surely matter to people. We will embed AI across every category and every product and every service to deliver one seamless, unified AI experience. Our device portfolio puts us in every moment of daily life, giving us unique consumer understanding."

Here's the opportunity and the problem:

  • Samsung ships more than 500 million devices each year and has a treasure trove of consumer data. But my confidence that Samsung can provide one unified experience isn't high. Samsung can't resist layering its Bixby assistant on top of Gemini. App conflicts are everywhere on a Samsung smart phone to the point where I ditched Samsung for Google's Pixel and Motorola's Razr. I don't need that UI disaster on my fridge.
  • It's not clear anyone is asking for AI features on their appliances. I just want my washer and dryer to work without some Samsung sensor freaking out. Confession: My Samsung dryer is a royal pain and works once in a while. If the Samsung appliance didn't come with the house it wouldn't make the cut.
  • AI everywhere sounds interesting on stage, but annoying in real life.
  • Ultimately, people will pay up for dumb appliances. Some appliance maker should just market with a line like: "Dumb appliances that just do what they're supposed to do reliably. Every time. For years."
  • Samsung has a good security ground game with Samsung Knox and on-device AI, but it's unclear whether consumers are going to be into sharing data with insurers. The data sharing will depend solely on the size of the discount. Details on the HSB discounts were sparse in Samsung's CES 2026 keynote.
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Enterprise technology 2026: 15 AI, SaaS, data, business trends to watch

Enterprise technology 2026: 15 AI, SaaS, data, business trends to watch

Enterprises will get all-you-can eat agentic AI pricing, data tools are going to be a headache, AI agents will look more like a feature than a revolution and physical AI will matter. Those are some of the trends to watch in 2026.

Here’s a look at the trends and predictions in enterprise technology for 2026 grouped by confidence levels.

High confidence

Agentic enterprise license agreements will become the norm as CxOs push back. In 2025, enterprise software vendors, which were worried about losing seats, introduced consumption models. The idea was that a hybrid approach would be the best of both worlds for CIOs. However, consumption models were unpredictable and CIOs, not to mention CFOs wanted predictability. Enter the agentic AI enterprise license.

Salesforce's Miquel Milano, president chief revenue officer, laid out the rationale behind Salesforce's AELA, Agentic Enterprise License Agreement. "AELA is for customers that have already experimented. They're ready to scale. They want to go all in so we agree on a flat fee, and then it's a shared risk," said Milano.

ALEA is all you can eat with Agentforce or whatever other cloud is thrown in. Of course, once you're all in Salesforce can better monetize the platform next contract. In 2026, it's highly likely you'll see similar arrangements from SaaS providers.

Here's the catch: SaaS providers may ink ALEAs at a loss as they play for the renewal (when you're completely locked in). Milano is looking at lifetime value of a customer. "If the customers are smart, they can rob the bank. They can really make a great deal out of that. We take the risk because we want our customers to be successful. I would love to have a customer where I price an AELA at $5 million incremental, and the customer has deployed so much that the deal is not profitable for me. If the deal isn't profitable for me, it means that the customer is the happiest customer in the world. And then I have another 20 years to monetize that customer," said Milano.

Enterprise data tolls and API economics are going to be a headache. Celonis is suing SAP over data access. In October, U.S. District Judge Vince Chhabria in San Francisco ruled the SAP must face the Celonis lawsuit. Toward the end of 2025, The Information reported that Salesforce was raising prices on apps that tap into its data. CIO.com noted that these connector fees are likely to trickle down to IT budgets.

As agentic AI is deployed and agents connect, there will be multiple skirmishes in 2026 over these data tolls. There will need to be some standard toll to cover compute costs, but enterprises need to keep in mind that they own the data. In some cases, your vendor may feel otherwise.

Connection fees are going to be the new cloud egress to move data. I'd argue that data fees are going to be the biggest risk to scaling AI agents.

Agentic AI is a feature and the real deal is decision velocity. This theme is Michael Ni's department, but decision velocity--how quickly smaller decision trees and processes can be automated at scale--will be a core theme. When Ni, in a video chat, said agentic AI was merely a feature I had two reactions. First reaction: How many pixels have been spent on a feature?!? Second reaction: Mike has a point. The game is decision velocity and you're task in 2026 will be to put the pieces in place to get there.

"What we're seeing is the first decisions are smaller decisions, automations on the backside of that leading to human engagement. Then we start to collapse these decision trees to get to some of the 5x, 10x improvements. We're seeing leaders actually able to achieve with decision automation," said Ni, who noted that 2025 was a year where a lot of the decision velocity building blocks were put in place.

In-house forward-deployed become a necessity. Software vendors—all cribbing a play from Palantir—talked up forward deployed engineers almost every time executives talked agentic AI deployments. In 2026, enterprises are going to realize they need their own forward-deployed engineers to work through data, process, architecture and AI automation. These engineers will know the business and industry better than the ones you’ll borrow from software vendors and services firms.

Medium confidence

The AI market will bifurcate as the bubble pops either in 2026 or 2027. Concerns about AI infrastructure capital expenses and debt will be what really scales in 2026. But don't get distracted with your AI plans. Chances are 2026 will highlight how the easy money in training LLMs, raising capital at a ridiculous clip and fabulous remaining performance obligations is over. That AI market, dominated AI's circular economy and OpenAI, will be completely different than the enterprise AI version. That productivity boom is just starting as AI and process automation converge.

Build will beat buy. The build vs. buy debate continues as AI agents make it easier to create applications you used to buy. In addition, build looks like a great option since customers are beginning to push back on SaaS deal inflation. SaaS costs go up annually. It's almost as bad as healthcare.

In 2026, there will be an inflection point where enterprises become convinced that applications custom to their use cases are the way to go. Sunk costs in enterprise systems will be abstracted away using agentic AI as a user interface.

AI benefits broaden out to more levels of the enterprise stack. Software vendors are going to show revenue and productivity gains from AI. On Wall Street, enterprise software vendors finally join the AI rally. Nvidia and AI infrastructure plays will be flattish in 2026.

Physical AI gets its moment. Manufacturing and industrial sectors start to leverage physical AI to deliver real value. In addition, physical AI breakthroughs will begin to rival the early days of LLMs. This physical AI focus drives optimism about robotics as well as edge AI applications.

Not absurd, but unlikely for 2026

  • Nvidia shares close the year flat to down year, but the fall isn't enough to result in real selling. Sales growth begins to slow as hyperscalers increasingly rely on their custom silicon. There's a concentrated effort in the industry to break Nvidia's hardware and software moat around AI.
  • AI infrastructure is overbuilt due to hardware and software advances that don't require as much compute and energy. Wall Street rewards companies like Apple that didn't go crazy building AI infrastructure. AI backlash builds as multiple NIMBY grassroots efforts thwart plans to build data centers in small towns and rural areas. Note I said something similar to this in 2025 to no avail.
  • OpenAI realizes it can't continually raise money forever goes on with an austerity push to show it can generate cash flow and become profitable.
  • Quantum use cases go mainstream in the enterprise as quantum supremacy comes early. It also becomes clear that superconducting quantum computing is the clear technology winner and that reality causes a mad scramble for companies focused on trapped ions, neutral atoms, annealing and other techniques.
  • Meta revamps its AI operations again once it's clear that its new management team and focus doesn't yield results. Meta's AI operations resemble the New York Mets, a massive payroll that doesn't deliver wins.
  • High memory costs create a buyers strike for PCs, servers and smartphones.
  • 2026 becomes one of the biggest years ever. for IPOs as Databricks, Anthropic, OpenAI, SpaceX and Stripe all go public. Two of those five headliners trade under their IPOs prices after 3 months.
  • TikTok usage plunges under new ownership as the US algorithm is tweaked.

Scorecard from 2025

Here's a look at my predictions for 2025 that worked out and other areas where my crystal ball was cracked. In 2025, I included probability of a prediction playing out.

On target:

  • 2025 was more volatile than usual.
  • AI productivity gains broadened in enterprises.
  • OpenAI and Microsoft became frenemies without a doubt.
  • Enterprises will try new SaaS revenue models and scream. Consumption sounds great...until you get the bill.
  • ERP comes under fire. ERP didn't go anywhere but is being abstracted.

Off base:

  • That alleged run on vendor consolidation never played out.
  • Agentic AI will usher in autonomous processes. We're clearly still in the early stages. The buy side is still wary of lock-in.
  • The AI data center buildout will stall. Actually, it just accelerated in a few days after I made that prediction.
  • Nvidia growth slows. Nvidia still faces the law of large numbers and more competition, but 62% revenue growth is pretty sweet.
  • Edge computing becomes more critical for AI workloads. It'll happen but sure didn't in 2025.
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DeepSeek's paper latest evidence AI muscle head era coming to end

DeepSeek's paper latest evidence AI muscle head era coming to end

DeepSeek published a technical paper co-authored by co-founder Liang Wenfeng that argues for a new architecture to train foundational models.

The paper, which details Manifold-Constrained Hyper-Connections (mHC), argues that a new architecture is needed to better scale deep learning without signal divergence. Granted, the mHC paper is wonky, but the key takeaway is that you can have large-scale training that's more efficient with better quality.

"Empirical results confirm that mHC effectively restores the identity mapping property, enabling stable large-scale training with superior scalability compared to conventional HC. Crucially, through efficient infrastructure-level optimizations, mHC delivers these improvements with negligible computational overhead."

Given that DeepSeek's paper landed the day after New Year's Day, it's unlikely to garner a ton of attention. However, DeepSeek's paper is just another development leading to the following: The muscle head era (error) of AI is coming to an end.

The AI market to date has been driven by muscle head logic. The answer for everything in the last two years has been more muscle. In AI's case that approach means more GPUs, more farm land going away, more energy usage, more water and by all means more data centers, debt and capital expenditures.

Almost a year ago, DeepSeek's LLM rattled the AI market because it appeared to be more efficient and trained without the latest and greatest from Nvidia. After an early freakout over DeepSeek, the US-driven part of the AI market went right back to the Stargate happy approach. Toward the end of 2025, investors were starting to question the capital expense and debt load behind the AI buildout.

In 2026, we're likely to see more engineering excellence and less muscle head logic. Here's some evidence to why that theory may play out.

  • Price and performance matter. LLM giants were busy diversifying their chip bases. Google's TPUs and Amazon Web Services' Trainium are going to be threats to Nvidia as inference becomes the main event.
  • Capital expenditures and debt loads are being questioned. Just ask Oracle and Meta.
  • Nvidia's not acquisition of Groq. Nvidia licensed Groq and hired damn near the whole company away because Groq's approach to memory and inference is more cost effective.
  • NIMBY is brewing. Yes, tech titans would pave over every inch of land for an AI factory, but you need power. Communities are going to become wary of paying higher electric bills for AI. Sen. Bernie Sanders of Vermont and Florida Gov. Ron DeSantis agree on little, but both agree AI's data center boom is a raw deal.
  • China is pushing new architectures that are easy on compute. The US has deprived China of Nvidia's best chips (until recently). As a result, China has eyed more efficient training and embraced open source. DeepSeek has the incentive to push new AI architectures. The US is more muscle over elegance.

DeepSeek's real legacy: Shifting the AI conversation to returns, value, edge | China vs. US AI war: Fact, fiction or missing the point?

These developments mean you can't just see DeepSeek's paper in a vacuum. It's just one more piece of evidence that AI is going to become way more efficient and that potentially means less compute.

 

 

 

Data to Decisions Tech Optimization Chief Information Officer