Category: Technology

The Israeli video personalization company is launching Strata, a basic model that reportedly creates separate, editable layers for text, animation, footage and actors instead of a single flat file. It represents a direct challenge to the architectural limitations of diffusion-based video generators.

Every AI video model currently on the market produces the same thing: a flat file. You can view it, share it, and crop it around the edges, but if you want to change the font, adjust an animation, or swap out the background, you’re basically starting over again.

This limitation has kept AI video out of professional production workflows where video was always created in layers, with separate tracks for text, motion graphics, footage and audio that can be adjusted independently until final rendering.

Idomoo, the Israeli corporate video personalization company, today announces Strata, a generative AI foundation model that it claims is the first model designed specifically for multi-layered video output. Instead of generating pixels, as Idomoo co-founder and CTO Danny Kalish puts it, Strata generates structure: independent layers of typography, animation, motion paths, and synchronized audio, all assembled into what the company calls a “production-ready video draft.”

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The difference is architectural. Standard diffusion models combine everything into a single tensor during generation; The spatial and temporal relationships between elements are baked into the pixels themselves.

According to Idomoo, Strata solves a different computational problem: it designs the entire composition, defining placement, contrast, movement, timing and pacing at all levels simultaneously, while enforcing brand guidelines. The resulting output can be edited at the layer level, just like a professional would work in Adobe After Effects.

Strata is part of Lucas, Idomoo’s AI video agent, which builds on the company’s existing next-generation video platform. One of his more technically specific skills is brand awareness: Lucas analyzes a company’s approved content to extract what Idomoo calls brand DNA, which includes design, narrative and assets.

Strata then applies this specification to every video generated through the platform, enforcing typography, motion cues, color values ​​and tone of voice throughout the output at scale. The intent is to eliminate the template workaround that most “AI wrapper” products currently rely on, where generated footage is limited to preset layouts.

Idomoo’s argument is that forcing content into templates results in a noticeable visual compromise; Instead, Strata designs individual blueprints for each video.

Personalization is the other axis. Because Strata’s output is layered rather than flat, individual data fields, names, account details, transaction histories and product images can be inserted into specific layers of the video composition in real time.

This is the core of Idomoo’s existing business model: the company’s platform already serves JPMorganChase, Verizon and American Airlines, among others, and generates personalized videos at scale for customer communications, onboarding and marketing.

Strata theoretically makes this personalization much more sophisticated because it occurs at the composition level rather than as an overlay on top of a pre-rendered clip.

The company is cautious about the scale of the launch. An early access version is currently being tested by several of its largest customers. It is available now via Lucas AI Video Agentbut Idomoo has not disclosed which customers are in the early access cohort, what benchmarks the model was tested against, or how it compares to standard diffusion models in terms of quality metrics.

The claim of “first base model specifically designed for layered video” is Idomoo’s own formulation and has not been independently evaluated. The Strata technology is patent pending.

It’s worth noting that Idomoo’s own platform documentation has so far explicitly stated that it uses standard AI base models rather than proprietary models. Strata represents a significant shift in this positioning: from a company applying AI to video to a company building foundational AI for video.

Whether the underlying architecture meets this framework will become clearer as enterprise customers move from early access to production deployments.

Founded in 2007 by Yaron Kalish, Danny Kalish and Assaf Fogel, the Ra’anana-based company has raised a total of $27 million, including a $9 million Series A in 2013 and an $18 million Series B in 2019. The company has been building its personalized video platform for enterprise customers for nearly two decades, giving it an unusual amount of structured video production data which it can train.

A new video (above) from South Korea shows the field testing and interaction capabilities of KAIST Humanoid v0.7, developed at the Korea Advanced Institute of Science and Technology (KAIST).

The impressive humanoid robot was developed at KAIST’s Dynamic Robot Control & Design Laboratory (DRCD) and uses actuators and other internally developed technologies.

In the video below, you can watch the bipedal bot walk, jog, and jump in an incredibly human-like manner. It also kicks a soccer ball at a goal (disappointingly, there’s no robot goalkeeper to challenge it) and performs a perfect moonwalk across astroturf. And it was the moonwalk that caused a stir in the comments on the video.

“Moonwalk was flawless,” one wrote, while another commented: “Okay, that was all impressive but you won me over with the moonwalk.”

In its robotics work, KAIST uses Physical AI, a form of AI technology that enables machines to understand and operate in the physical world, and helps explain why robots like the KAIST Humanoid v0.7 appear to move in such a human-like manner.

Instead of just “thinking in words” like typical AI, physical AI gives machines a sense of space and timing in real-world environments.

As part of KAIST’s broader collaborative intelligence initiative led by Young Jae Jang, the approach trains robots and systems to continuously learn through simulation and real-time feedback, rather than relying solely on huge historical data sets.

Essentially, physical AI connects the brain and body through the tight integration of software intelligence with hardware such as motors and sensors, so that the machines not only compute but also act, react and collaborate in complex environments, whether as part of fully automated factories or in humanoid robots that, for example, kick a ball.

Engineers are refining the KAIST Humanoid v0.7 with the goal of improving its mobile and dexterous capabilities, building on its existing walking and dynamic movement capabilities. Further integrating AI with mechanical hardware aims to make the robot perform more complex tasks such as carrying objects or operating machines, thus integrating physical AI into real-world humanoid robotic applications.

KAIST is one of South Korea’s top universities and is often compared to leading global technology schools such as MIT in the USA. KAIST was founded in the early 1970s to promote Korea’s scientific and technological growth. The focus is on research in areas such as AI, robotics, physics and engineering.

The indictment of Super Micro’s co-founder exposes not only a $2.5 billion scheme, but also a system that was never designed to stop such a scheme.

Somewhere in a rented warehouse in Southeast Asia, a man was using a hairdryer on a server box. Do not dry. To loosen the adhesive on a serial number sticker so that it could be carefully peeled off and pressed onto another machine, a machine that was never plugged in, never powered up, and never intended to reach its declared destination.

The real servers, which contain Nvidia’s most advanced AI accelerator chips, had already been repackaged in unmarked boxes and shipped to China. The doll, dressed in borrowed labels, waited for the examiners.

This scene, reconstructed from surveillance footage cited in a federal indictment unsealed on March 19, 2026, is the most accurate picture we have yet of how America’s semiconductor export controls actually work in practice. Not in theory, but in practice. It turns out the answer comes down to a hairdryer.

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Three men are charged in the indictment: Yih-Shyan “Wally” Liaw, 71, Co-Founder, Board Member and Senior Vice President of Business Development the super microcomputer; Ruei-Tsang “Steven” Chang, 53, general manager of the company’s Taiwan office; and Ting-Wei “Willy” Sun, 44, a contractor described by prosecutors as a “fixer.”

Between 2024 and 2025, they are said to have orchestrated the redirection of servers worth around $2.5 billion, many of which were assembled in the USA and integrate Nvidia GPUs, to customers in China via a front company in Southeast Asia.

At least $510 million in hardware was shipped during a single six-week window in spring 2025. Liaw and Sun were arrested. Chang, a Taiwanese citizen, remains a refugee.

The charges include conspiracy to violate the Export Controls Reform Act, conspiracy to smuggle goods out of the United States and conspiracy to defraud the government. These crimes are punishable by a total maximum prison sentence of 30 years.

Super Micro, the publicly traded San Jose company that makes the hardware at the center of the scheme, was not named as a defendant. It placed Liaw and Chang on administrative leave and ended their relationship with Sun. It said it had cooperated with investigators and maintained a “robust compliance program.”

This sentence deserves to stay with you for a moment.

According to the indictment, the defendants and their co-conspirators communicated using encrypted messaging applications to coordinate what quantities of servers to order, which locations in China to ship them to and, crucially, how to hide the plan from the company’s own compliance team.

When an internal audit was planned, they deployed thousands of non-functioning server replicas in a warehouse rented by the front company. When a U.S. Department of Commerce inspector arrived to inspect the same facility, he used the same props and used heat guns to exchange labels and serial numbers before the visit.

The inspector, the indictment says, did not see the actual servers because they had already been sent to China. According to the public prosecutor’s office, an auditor from the company who should have been on site for a separate inspection was “outside the company and having fun at the expense of the fake company.”

The gap that was never a secret

The transshipment route through Southeast Asia is not a discovery. It is a well-known, documented and repeatedly highlighted feature of the export control architecture – one that U.S. trade analysts, think tanks and the Commerce Department itself have been warning about for years. Countries such as Malaysia, Singapore, Vietnam and Thailand have historically, as East Asia Forum analysts noted earlier this month, “lacked the enforcement infrastructure or political will to strictly monitor re-exports.”

According to an analysis published by The Diplomat, between April and July 2025, Vietnamese authorities intercepted more than 2,000 shipments that were falsely labeled as “Made in Vietnam” but were traced to Chinese factories. Malaysian tech hubs in Penang and Johor were reported for similar diversion practices.

DeepSeek, the Chinese AI lab that became a household name after releasing its model in January 2025, was accused in a report by Tom’s Hardware of setting up “ghost” data centers in Southeast Asia to pass exams and then passing on the GPUs.

According to an investigation by the Financial Times, China secured around $1 billion in advanced AI processors in the three months immediately following the last major tightening of U.S. export controls.

In other words, the pattern is not deviant. It’s structural. Controls are primarily enforced at the point of sale and at first shipment and are based almost entirely on the buyer’s declared end use and the downstream compliance of each intermediary in the chain. When the incentive to lie is hundreds of millions of dollars, there are limits to the honor system.

The company that survives itself

The appearance of Super Micro in this case is not a surprise, to say the least. The company has amassed a regulatory history that would be notable in isolation, but upon closer inspection suggests something more systemic.

In 2018, the company was temporarily delisted from Nasdaq for failing to file financial statements. In 2020, the company paid a $17.5 million fine to the Securities and Exchange Commission for what the agency called “widespread accounting violations”: more than $200 million in misrecorded revenue and understated expenses, which artificially inflated sales and profit margins.

The co-founder now facing federal charges, Wally Liaw, resigned from the company during this period. He returned as an advisor in 2021, was named senior vice president in 2022, and rejoined the board at the end of 2023.

In 2024, short seller Hindenburg Research released a report alleging new accounting irregularities, undisclosed related-party transactions, and, most notably, violations of U.S. export controls.

Ernst & Young, the company’s auditor, resigned shortly thereafter, saying it could no longer vouch for the accuracy of management’s financial representations. Super Micro has commissioned an independent special commission to review; No evidence of fraud was found.

Despite all this, Super Micro remained in the S&P 500. Sales in the last quarter were $12.7 billion.

There is a legitimate question in this number: At what point does the sample become a product? The compliance errors keep occurring. The managers involved always return. The stock continues to recover. The hardware keeps moving.

Whether Super Micro’s board and remaining leadership can provide a credible answer to this question will be of enormous importance not only to investors, but also to its credibilityThe possibility of the entire export control regime that they allegedly helped to circumvent.

Enforcement when the wind eases

The irony of this week’s indictment lies in its timing. The Trump administration in recent months has quietly relaxed export control stances that made shipping the hardware in question illegal.

In December 2025, the White House announced it would allow certain chips to be sold directly to approved customers in China.

In January 2026, the Bureau of Industry and Security released revised licensing rules that allow for case-by-case review rather than acceptance of denial for exports of previous generation AI hardware to mainland China.

A rule known as the “Affiliates Rule,” intended to close loopholes surrounding Chinese subsidiaries, was suspended for a year almost immediately after it was published.

This creates a strange political geometry. The Justice Department is prosecuting men for sending chips, which US policy is beginning to allow at the same time.

There is a version of the story in which this tension resolves smoothly: the government enforces the current rules while adapting them to the future, and the two paths do not contradict each other.

There is another version in which enforcement becomes selective, a tool to signal toughness while the underlying architecture quietly weakens. Which version actually unfolds is a question worth watching closely.

Congress was watching, and not quietly. The BIS received a 23% budget increase for fiscal year 2026, with bipartisan support and explicit funding for semiconductor law enforcement. Several lawmakers have sought congressional oversight of export permits, frustrated by what they say is inconsistent executive authority.

What none of this solves is the fundamental architecture of the problem. Export controls enforced at the point of sale, based on declared end use and monitored by corporate compliance teams who can be fooled with a hairdryer and a rented warehouse, are ultimately not a system designed for the scale of economic incentives currently in play. The chip war has raised the stakes far beyond the level the honor system was intended for.

The servers have already arrived. The stickers have been carefully reapplied. The dummy machines were ready for inspection. And somewhere in a data center in China, the real hardware is running, training models, refining weights, closing the gap.

The inspectors are still on the way.

Google is once again testing how artificial intelligence can transform the way users interact with information online – this time by changing one of the most fundamental elements of search: headlines. The company has begun experimenting with replacing original news headlines in search with AI-generated alternatives, raising concerns among publishers and questions about accuracy and editorial control.

AI is starting to rewrite the “10 blue links” of the web

In a recent experiment, Google started showing AI-generated headlines in its traditional search results instead of publishers’ original titles. This represents a significant departure from previous practices where Google shortened or slightly modified headlines for clarity.

Reportedly, these rewritten headlines can sometimes change the meaning or tone of the original article. In some cases, nuanced or critical headlines were shortened to generic or misleading wording, potentially giving users the wrong impression of the content before they even clicked on it.

Google describes the feature as a “small and narrow experiment” aimed at improving search results matching user queries and increasing engagement. However, the company has not revealed how extensively it is testing the feature.

Why this is a concern for publishers

Headlines are a crucial part of journalism – they are carefully crafted to accurately convey a story while attracting readers. By replacing them with AI-generated versions, Google is effectively taking control of how articles are presented to users.

News Unsplash

Publishers fear this could undermine their editorial voice and credibility. If an AI-generated headline misrepresents a story, readers may blame the publication rather than Google, potentially damaging trust.

There are also concerns about transparency

Currently, there is little to no evidence as to whether a headline has been altered by AI, making it difficult for users to distinguish between original content and machine-generated content.

This development follows similar experiments at Google Discover, where AI-generated summaries and headlines have already been criticized for inaccuracies and misleading wording. For everyday users, the change could subtly alter the way information is consumed. Headlines play an important role in shaping first impressions, and even small changes in wording can influence how a story is interpreted.

Google News Unsplash

When AI-generated headlines prioritize engagement over accuracy, users are more likely to click on content that isn’t quite what they expected. In some cases, they may also miss important context or nuance that was present in the original headline.

At the same time, Google argues that AI can help make headlines more relevant to searches, potentially improving discoverability and making it easier for users to find what they’re looking for.

What’s next?

While the current rollout is limited, the experiment could signal a broader shift in the way Google integrates AI into search. The company has historically introduced features as small tests before expanding them into full-fledged products.

Publishers and industry observers will likely push for clearer labeling, more transparency and possibly opt-out mechanisms as the feature expands. Meanwhile, regulators may also pay closer attention to how AI-generated content is presented, particularly if it impacts the distribution of news and public information.

For now, the experiment remains a “canary in the coal mine” — a sign of how AI could increasingly influence not only what users see online, but also how that information is compiled and understood.

The Rijen-based startup, which retrofits existing sprayers with nozzle-by-nozzle PWM control, will use the capital to commercialize its LeapEye camera system and scale LeapBox internationally from Europe to Canada.

The idea behind BBLeap is disarmingly simple: Most agricultural sprayers treat an entire field as a unit, applying the same dose of pesticide, herbicide or fertilizer regardless of what individual plants actually need.

BBLeap was designed under the premise that this is wasteful, inaccurate, and unnecessary, and that the technology to do something better has been around for so long that there’s no good excuse not to use it.

The Dutch startup based in Rijen in North Brabant has raised €5 million in a round led by Utrecht-based private equity firm ESquare Capital, with co-investment from Yield Lab Europe, an impact-focused agri-food venture capital fund backed by the European Investment Fund.

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Existing shareholders, including BOM (the Brabant Development Agency, one of the company’s early backers) and Beheermaatschappij Vriend also participated. BBLeap will use the capital to complete the commercial launch of LeapEye, its large-scale arable camera detection system, and expand LeapBox internationally, adding Canada to its existing presence in Europe and Australia.

BBLeap was founded in 2019 by Peter Millenaar, Rieks Kampman and Martijn van Alphen, three people with backgrounds in the agricultural machinery industry who previously worked together at a sprayer manufacturer. Millenaar, who serves as CEO, has described the company’s mission as “farming at plant level,” giving each individual plant exactly the dose it needs rather than spreading the average across a field.

The company’s core product, the LeapBox, is a modular pulse width modulation (PWM) system that can be retrofitted to any existing sprayer, regardless of brand or age, and independently controls each nozzle to maintain constant pressure, droplet size and precise volume.

A cloud-based platform, LeapSpace, processes high-resolution prescription maps generated from drone, satellite and sensor data.

The second product, LeapEye, expands the system’s capabilities with real-time detection: a large-area camera that scans crops as the sprayer moves across a field, detects what needs to be treated, and adjusts the performance of each nozzle accordingly.

According to the company, depending on the application, chemical savings of between 20 and 99 percent and an increase in capacity of up to 40 percent are possible. These figures are derived from proprietary materials and have not been independently verified.

What has received independent validation is the technology itself: BBLeap recently received approval from Germany’s Julius Kühn Institute (JKI), the Federal Research Center for Plant Protection, for its PWM spray approach, a significant regulatory endorsement in the European agricultural market.

The company says it already has more than 200 users operating BBLeap systems in Europe and Australia, with rollout currently underway in Canada. Both the number of users and the geographical information come from press materials and have not been independently confirmed.

What is independently documented is the breadth of the partnership: BBLeap has worked with precision farming data platform OneSoil in a global integration that allows farmers to convert satellite prescription cards into BBLeap spray orders in minutes, and has established relationships with sprayer manufacturers including Denmark’s Dammann.

“BBLeap offers 100 percent certainty of spraying exactly what is needed, delivering good applications, fewer diseases and fewer weeds, while using significantly fewer chemicals,” Peter Millenaar said in a statement accompanying the announcement.

The investment comes at a time when regulatory pressure on the use of agricultural chemicals is increasing in Europe. The EU’s “Farm to Fork” strategy aims to halve pesticide use by 2030. Precision spraying technologies are one of the cleaner routes farmers can take to achieve this goal without sacrificing yield.

For BBLeap, the challenge is to translate a technology proven in field trials and early adopters into a commercially repeatable product that can be sold, installed and supported at the scale investors are now betting on.

Hydrogen power has never found a home in your car, but it could finally come into its own in a drone. Researchers in Norway have built a heavy-lift drone that runs on hydrogen and replaced batteries with a fuel cell to solve the range problem that keeps most commercial drones grounded.

The prototype from SINTEF, a Scandinavian research institute, is aimed at tasks where battery-powered drones are not sufficient. Think about inspecting remote power lines after a storm or searching for missing hikers in bad weather. Lead research scientist Federico Zenith says the goal isn’t to replace your weekend flyer. It’s about tackling missions that today’s drones simply can’t accomplish.

Why fuel cells beat batteries and gas

Instead of building from scratch, the SINTEF team started with a heavy battery-powered model and swapped in a fuel cell and hydrogen tank. Zenith describes the transition as straightforward, a path that could allow operators to upgrade existing equipment rather than buying everything new.

Testing the drone SINTEF

At the moment, their prototype is a rare sight. According to Zenith, it is the only hydrogen drone flying in Norway and, as far as the team knows, the only one in all of Scandinavia. This makes the institute a rare test case for what hydrogen can actually do for flight times.

The fuel cell also outperforms the gas-powered alternative. Conventional engines require frequent replacement and extensive maintenance. According to Zenith, a fuel cell runs for at least a thousand hours and is easier to replace when it eventually wears out.

Where hydrogen drones actually make sense

Longer flight times enable high-stakes work. The SINTEF team sees the hydrogen prototype inspecting power lines after storms, a task that now often requires a helicopter. If a tree falls on a line in bad weather, sending a crew up is risky. A hydrogen drone could take off immediately and help restore power more quickly.

SINTEF

Search and rescue services are also a clear solution. The same range that allows a drone to follow power lines from transformer to transformer allows it to search vast areas for a lost hiker. The researchers also mention mapping, snowpack monitoring for flood forecasting and landslide monitoring.

Here too, the financial mathematics is changing. A fuel cell is still expensive, admits Zenith. But compared to manning a helicopter for the same mission, the drone becomes a cost-effective option. This bill could finally give hydrogen the breakthrough it never had in passenger cars.

What’s next for hydrogen flight?

The hydrogen drone has flown, but cannot yet cope with a real Norwegian winter. The fuel cell in the prototype is only designed for use above freezing and in dry conditions, which means, as Zenith points out, there are not many flyable days in Tröndelag County at the moment.

Weather protection is the next big task. The SINTEF team is actively seeking funding and partners to undertake this work. The goal is to find out how many hours they can keep a drone in the air under real northern conditions, not just in a lab.

The potential here is obvious. If they can solve the weather problem, hydrogen drones could quietly take over the tasks that are too distant, too dangerous or too expensive for helicopters and battery packs. Technology that has stalled on the highway may finally find its purpose in the sky.

Meta’s Creator Fast Track program guarantees three months of pay to established creators willing to build a following on Facebook, after the company paid out a record $3 billion to creators in 2025.

Facebook has a creator problem that three billion monthly users can’t solve. The platform is huge, but the creators driving the short-video economy and building loyal audiences on TikTok and YouTube have largely overlooked it.

Starting a new platform from scratch is daunting, and Facebook’s history with creators is so complicated that even those who have heard the pitch have reason to hesitate.

On Wednesday, Meta Creator launched Fast Track, a direct attempt to address this hesitancy with cash. The program offers established creators with audiences on other platforms guaranteed monthly payments for three months in exchange for publishing Reels on Facebook.

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Creators with at least 100,000 followers on Instagram, TikTok or YouTube can earn $1,000 per month; Those who reach one million followers on any of these platforms will receive $3,000 per month.

The admission requirements are not demanding. Creators must post at least 15 Reels to Facebook within 30 days, spread over at least 10 different days. Content does not have to be exclusive to Facebook and may include AI-generated material as long as it is original to the creator.

Participation will also give you immediate access to Facebook Content Monetization, the broader invitation-only program that pays based on content performance. This means that the income will continue even after the three-month guarantee period has expired.

The program comes alongside a number that Meta is clearly happy with: In 2025, Facebook paid content creators nearly $3 billion through its monetization programs, a 35% increase from the previous year and the highest annual payout on record.

That compares with $2 billion in 2024, a figure the rest of the world independently confirmed in February. The number of creators earning more than $10,000 annually on Facebook has increased by over 30% compared to last year.

The breakdown of where this money went is also noteworthy.

Sixty percent of the $3 billion went to Reels, while the remaining 40 percent was split between stories, photos and text posts. This last detail is important to the Creator Fast Track pitch: Unlike TikTok and YouTube, which are fundamentally video-first platforms, Facebook Content Monetization pays for almost everything a creator posts.

A writer who shares text posts, a photographer who posts stills, or a creator who works primarily in Stories can all make money from the platform without having to commit to video production.

Monetization of Facebook content itself has increased dramatically over the past year. According to a February 2026 analysis of Rest of World Meta Monetization Archive data, the program grew from around 2.7 million participants to 12 million in just over a year, with Indonesian-language accounts representing the second largest cohort after English.

The global scale of this expansion is part of what makes the $3 billion figure credible, and part of what Facebook wants to use to attract creators who would otherwise dismiss the platform as irrelevant to a younger audience.

Alongside the program, Meta is also introducing new metrics to help creators understand their earnings more accurately.

This includes a metric for qualified views, views of content that can make money, an earning rate that shows the approximate compensation per 1,000 qualified views, and a non-qualified views breakdown that explains why certain views don’t generate revenue.

The clearer feedback loop is intended to help creators optimize the performance of their content rather than simply guessing why their payouts vary.

Creator Fast Track’s strategic logic is not subtle. Facebook has been pushing Reels hard since 2020, positioning it as a response to TikTok’s dominance in short-form videos.

But Reels require content, and content requires creators willing to invest time in building the platform. The guaranteed payment model removes the risk that typically discourages established creators from experimenting with a new home: the fear of posting consistently for months and earning next to nothing while still building an audience.

For Meta, which reported advertising revenue of around $160 billion in 2025, writing checks to a few thousand established YouTubers is a rounding error compared to the potential gain of a Facebook feed with more YouTubers.

Whether YouTubers bite depends on something harder to measure than money: whether Facebook’s audience and long-term monetization potential are worth the effort of maintaining another profile.

The $1,000 per month tier, which requires 100,000 followers to qualify, is not a transformative sum for a YouTuber of this magnitude. The $3,000 per month tier is more meaningful, although most YouTubers at the million-follower level weigh that against what they’re already making.

What the program clearly offers is a trial run with no downsides, three months of guaranteed income, to see if Facebook’s reach can surprise you.

For athletes, game improvement is not just about techniques, but is the result of continuous practice. As a reliable training partner, quality coaching with a coordinated schedule can be quite difficult, especially for players who train independently.

This gap has been a key focus that sports technology has worked to overcome.

Pongbot is a prominent investor founded in 2019 that has developed AI training robots aimed at training smarter, improving endurance and speed so athletes are game-ready even when training solo.

The robot training system combines detailed technology with AI automation and can effortlessly adapt to the player’s movements step by step.

Athletes can also customize their training sessions via the easy-to-use mobile app, which includes extensively analyzed game data. Pongbot focuses on the global growth of the smart sports ecosystem in collaboration with gaming communities around the world, such as Germany, Australia, the United States, Italy, etc.

Scaling table tennis technology to an AI tennis court

Pongbot’s first innovations began in the table tennis training space with robotic ball servers to improve reflexes, spin control and training consistency. This was accompanied by the realization that other serving machines also had similar limitations in their function; repeated ball feeds without adapting to the player’s movements.

Training proved to be predictable and did not reflect real games.

To change this, Pongbot began developing training robots that leverage extensive gaming data with its proprietary AI system, the PongSmart algorithm. This results in the training robots accurately recognizing the players’ positioning and then dynamically adjusting their ball throw. This led to the innovation of the Pongbot Pace S Series, an AI tennis training system that overcomes all traditional limitations of ball machines.

Since its launch, the Pace S Series has received a great deal of positive response, raising more than $2.7 million on Kickstarter, securing 69 research and development patents, and becoming the No. 1 technology and sports campaign on Kickstarter 2024.

This ultimately earned Pongbot widespread recognition from sports influencers as well as professional tennis media Tennis.com.

NextGen Robotic Tennis Kit: Pace S Pro

Among all Pongbot’s innovations, the focus is Pongbot Pace S Pro, a flagship tennis series specifically designed to recreate a rally in real time on the court, adapting to each player and their practice techniques.

Pongbot

What makes it different?

Not only are balls fired at the same designated location during practice; Using ultra-wideband tracking technology (UWB), he can accurately position his throw up to 10cm. In addition, the 100 Hz tracking rate allows the robot to monitor movements three times faster than standard camera-controlled systems. Works absolutely great in both low light and bright outdoor courts and sets a completely new benchmark for tennis ball machines as automated trainers.

This offers athletes a game-like competition without the entire experience feeling too mechanical and is ideal for individual training.

Training sessions evolve with the players

Pace S Pro analyzes its data to perfect timing, tracking and intensity during practice drills. This means players who train alone can easily execute complex punch combinations or try out tricky sequences without having to worry.

A feature that makes it even more interesting is the Recovery Trigger, a mechanism that only fires the next ball once the player is back at their assigned spot on the field. This shows that the system learns with each practice session and adapts to the practice patterns in a very short time, improving training through automation.

It can also ensure natural tempo through realistic practice:

• Using game-like speed to refine advanced footwork for athletes
• Beginners who play for recreation can play without becoming overwhelmed

Intelligent exercises provide professional-level thrills

By bringing intelligent tennis to the court, the Pongbot Pace S Pro goes beyond just intelligent tracking. Pace S Pro features a starting speed of up to 80 miles per hour and spins of around 60 per second, which can help tennis players train their backspin, strong topspins as well as combination shots.

It is fully designed for training across the entire court, from baseline to net, including over 564 tennis training routines approved and designed by professional coaches; Ready and customizable for players directly from the companion app. Easily set up a one-on-one match right from your phone.

Smart match planning via a mobile app can also help players develop an individual playing style or replicate the training styles of tennis prodigies such as Nadal, Djokovic or Federer to experience a real game-like thrill during their training session. Even if the training device is offline.

Connected training beyond the machine

Pongbot

For Pongbot, the training robots represent a huge networked training system and are not just a machine. By combining the use of this intelligent training robot with a mobile app for setting fairways, the following is possible:

• Access to numerous user-generated training practices
• Points and rewards with milestones
• Track progress using training game data
• Download exercises or share them with the global sports community

Additionally, with the introduction of future wearable sensors as part of advanced AI alongside tennis ball pickers or ball connectors, over-the-air updates may lead to smarter training practices.

Table tennis robot joins the game

Although Pongbot’s latest product range focuses on tennis, the table tennis range remains the brand’s core component.

Pongbot Nova S Pro is a portable ball machine designed for players looking for a compact but equally powerful training partner. With a delivery rate of up to 30 to 90 balls per minute between 2 and 15 m/s, with combined top and back spin, it is designed to be backpack-friendly.

By connecting to the mobile app, players can access over 264 professional training drills to easily customize their game plan.

This is far from easy, but there is more. The Pongbot Omni S Pro is a series with 360° spin adjustment with rotations of up to 100 per second at speeds of up to 15 m/s. Don’t miss the 396 preset exercises supported by unlimited custom sessions.

Next up is the Pongbot Halo S Pro, a floor-standing training robot for intensive exercises. This series serves to support and model tactical processes in addition to calculating footwork and swing coordination.

It features wide oscillation, over 576 preset routines that can be customized by the player, and has 21 speed levels. It is the absolute premium design with app plus remote control and ball net for professional table tennis training.

Both models, Omni and Halo, were manufactured with the valuable contributions of Chen Bin, a former coach of the Chinese national table tennis team, to ensure that these robot trainers accurately reflect professional techniques.

Get ready with the Spring 2026 sales campaign

Just in time for the start of the training season, Pongbot has also launched its 2026 spring sales campaign with the slogan “From Rusty to Done – Get Back in Shape This Spring.” From March 11 to April 11 (PST), Pongbot is offering up to 45% off its tennis and table tennis training robots.

The highlight is its flagship model, the Pongbot Pace S Pro, with a massive price drop from $1,999.99 to $1,199.99, among others, during this sale.

In addition to the exciting offers, customers can also receive free accessories or surprise vouchers as a Pongbot newsletter subscriber or spin the wheel of fortune to receive more offers and a free order. The campaign also includes a Wish Wall competition, a chance for three random participants to win a wish from Pongbot.

This comeback season, the campaign offers athletes the opportunity to train smarter with improved training robots without burning a hole in their pockets.

Pongbot redefines intelligent training for beginners and professional athletes alike. The combination of automation and sports routine is a further development. These robotic training devices blur the line between professional coaching and solo training. Players will have to get used to real-world game-like challenges that could soon make these intelligent training robots as indispensable on the field as bats and balls.

The platform was founded by two French serial entrepreneurs who spent decades in Romania. The aim of the platform is to be a trust-by-design alternative to X and Facebook. The public launch is planned for May 2026.

A new social media platform that embeds real-time fact-checking directly into the user experience has raised €300,000 in pre-funding from Fil Rouge Capital, the Croatia-founded early-stage venture fund that expanded to Romania in 2025.

The startup, called eYou, was founded in Bucharest in 2026 by Grégoire Vigroux and Jasseem Allybokus and plans a public launch in May. A waiting list is already open on eyou.social.

The platform’s central proposal is simple: when a user clicks on a post, an AI-generated review appears in a pop-up, drawing on what the platform describes as credible and neutral sources, summarizing the veracity of the claims made. The goal is to give users the ability to challenge misinformation in real time without interrupting the flow of the conversation itself.

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eYou also introduces a so-called transparency level for the feed algorithm. Instead of hiding its recommendation logic, the platform allows users to view and edit the profile the algorithm creates about them, with the option to consciously expand the presence of their content and leave algorithmically reinforced echo chambers. b

Both features are direct responses to the two criticisms most often leveled at mainstream social media: that they spread misinformation faster than they can correct it, and that they trap users in ideological bubbles they never intended to enter.

“Unlike traditional social networks that increase engagement at all costs, eYou was built with trust first. Social media was originally intended to connect people and democratize information. But over time, it has also become a powerful driver of polarization and misinformation. We believe there is a real need and urgent demand for a new kind of platform based on transparency, accountability and trust.” said Grégoire Vigroux, co-founder and CCO of eYou.

The platform was designed with GDPR compliance and European data protection standards at its core, a design choice the founders make as a differentiator from dominant US platforms and as an adaptation to the regulatory environment in which European users increasingly expect to operate.

Jasseem Allybokus, co-founder and CEO, brings technical expertise from his previous role as CTO at Visiperf, a French digital marketing technology company serving more than 300 brands in more than 15,800 retail locations and 4,000 geographical zones. He also co-founded Ecrilib, a creative writing community platform.

“Today, most social platforms are designed to show users more of what they already agree with. This reinforces echo chambers and allows misinformation to spread faster than facts. eYou introduces a completely different approach to online discussions, based on European principles of transparency, accountability and engagement with different viewpoints.” said Jasseem Allybokus, co-founder and CEO of eYou.

Vigroux is one of the most prolific serial entrepreneurs in the Romanian startup ecosystem. In 2007, he and business partners founded CallPoint New Europe, a BPO company that grew to more than 1,000 employees and was acquired by TELUS International, the Canadian global customer experience company, in 2012.

He served as co-founder and vice president of business development at TELUS International in Europe and remained on the board until his retirement as a shareholder in 2017. The company, which operates as TELUS International Europe, currently employs around 5,000 people in Romania and Bulgaria.

Among other things, he co-founded BonApp, a mobile app for food waste, and Fenix.eco, a renovated smartphone shop that was sold to Recommerce within 14 months of its launch.

The €300,000 round comes from Fil Rouge Capital’s accelerator program. The originally Croatian fund, now expanded to Romania with Matei Dumitrescu as local venture partner, operates a program that offers up to 300,000 euros in pre-financing funding for early-stage companies, with a path to up to 1 million euros in follow-on investments in VC.

Fil Rouge Capital has backed more than 170 companies since its founding in 2014 and lists portfolio exits including DocPlanner and happn.

“The founders bring strong entrepreneurial experience, a clear vision and address one of the most important challenges facing digital platforms today: trust. eYou has the potential to become the leading European social media player.” — Matei Dumitrescu, partner at one of Fil Rouge Capital’s funds

The platform will be available on iOS, Android, mobile and desktop web from its public launch in May 2026. eYou is open to users around the world, although its architecture, regulatory design and investor positioning are explicitly European.

One of the most talked about AI video generators in recent weeks may not be coming as soon as expected. According to a new report from The Information, TikTok parent company ByteDance has reportedly paused the global rollout of its video generation model Seedance 2.0 after getting embroiled in copyright disputes with major Hollywood studios and streaming platforms.

Byte Dance

Seedance 2.0, which launched earlier this year, spread quickly across the Internet because of its ability to create highly realistic video clips from simple command prompts. The model can create short videos from text or images, making it one of the newest entrants in the fast-growing text-to-video AI competition, alongside tools like OpenAI’s Sora and Google Veo.

Why is ByteDance delaying the launch?

The delay appears to be related to growing legal pressure from the entertainment industry. Several Hollywood studios and streaming companies, including Disney, Netflix and Paramount, reportedly expressed concerns that the model may have been trained on copyrighted film and television content without permission. Some AI-generated clips circulating online reportedly featured recognizable characters or actors from popular franchises, leading to legal warnings.

Disney has reportedly sent a cease-and-desist letter to ByteDance, claiming that the model’s training data used copyrighted works and that some output reproduced protected intellectual property. Given these concerns, ByteDance has reportedly paused its planned global rollout, expected around mid-March, while engineers work on safeguards to prevent unauthorized use of copyrighted material.

Why has Seedance 2.0 attracted so much attention?

Seedance 2.0 quickly gained attention after its debut due to its ability to create short cinematic videos with realistic movements, camera movements, and characters. Viral clips featuring scenes with recognizable actors and characters sparked both excitement and concern across the creative industry.

The situation also reflects a growing tension in the AI ​​space, where powerful generative tools are advancing rapidly and developers and studios are wondering how training data is sourced. As a result, legal challenges may increasingly determine how and when these AI models reach the public.