Lucid’s European robotaxi deal now has a driver. Bolt announced today that its fleet of at least 25,000 autonomous Lucid vehicles will run Nvidia’s Alpamayo Stack self-driving software, starting with a data-collection program in Madrid in 2027.
That gives Lucid two robotaxi customers on two different autonomy systems: Nuro’s software for Uber’s Gravity robotaxis in the US, and now Nvidia’s for Bolt in Europe.
Germany-based robotics firm Agile Robots reportedly plans to produce up to 2,000 humanoid robots next year through a fresh partnership with Nvidia, targeting universities and corporate research labs.
The collaboration was announced at Nvidia’s GTC conference in Berlin. Agile CEO Zhaopeng Chen told Reuters the pair are set to begin production of the Agile ONE S and ONE SN humanoid robot models by the end of 2026, expecting to manufacture between 1,000 and 2,000 units. Stanford University and ETH Zurich are among potential customers.
The Agile ONE SN, with the N standing for Nvidia to denote the chipmaker-specific configuration, combines Agile’s humanoid hardware with Nvidia’s Jetson Thor onboard computing platform and Isaac GR00T robotics AI model. It features five-fingered hands, cameras and other sensors to support dexterous manipulation and interaction with the physical environment.
Standing 1.4 metres tall and weighing around 40 kilograms, the robot is designed as a smaller alternative to full-sized humanoids. Nvidia said the robot intends to simplify the integration of hardware, simulation, training and deployment tools on a single platform, “cutting setup time from weeks to days”.
Spencer Huang, Nvidia’s product director for robotics, told Reuters the standardised configuration could save researchers two or three months of work procuring separately purchased components. “If we can bring researchers something that’s already 80% of the way there, it accelerates their development,” he said.
Nvidia said Agile’s ONE SN is scheduled to become available in early 2027, as competition intensifies among European humanoid developers.
ChatGPT moment Alongside the partnership, the chipmaker also revealed its expanded robotics development platform, Nvidia Isaac, equipped with new tools for training and deploying AI-powered machines. The expanded platform includes Isaac OS, an open-source runtime framework, and Isaac Lab 3.0, a robot learning framework designed to train and refine robot skills. The company also introduced new reference workflows and simulation resources to speed up development.
“General-purpose robotics is advancing at extraordinary speed — the ChatGPT moment for robotics is fast approaching,” noted Jensen Huang, CEO of Nvidia, adding the platform would give developers “the models, data, simulation tools and computing systems to bring physical AI to the world’s largest industries”.
The chipmaker added European robotics players including UK-based Humanoid, French start-up Hugging Face and Swedish firm ABB Robotics are applying its technologies including Nvidia Isaac to industrial autonomous machines.
Chi gioca su PC conosce bene quella fastidiosa situazione in cui un videogioco appena installato richiede diversi minuti per preparare gli shader, oppure presenta improvvisi scatti anche quando la scheda grafica sarebbe perfettamente in grado di gestirlo. Il problema riguarda il modo in cui vengono compilati gli shader, piccoli programmi che la GPU utilizza per elaborare luci, ombre, materiali ed effetti visivi, e come vi avevamo anticipato qualche giorno fa, ora è disponibile una novità che va a risolvere proprio questo problema.
Con l'arrivo dei nuovi driver NVIDIA GeForce 621.01, questo inconveniente potrebbe diventare molto meno frequente grazie al supporto per Advanced Shader Delivery, una tecnologia sviluppata da Microsoft che cambia il modo in cui gli shader vengono preparati e distribuiti ai computer.
Normalmente, ogni PC deve compilare gli shader in base alla propria configurazione hardware e software, e questa è un'operazione che richiede tempo e che, quando avviene durante una partita, può provocare improvvisi picchi di utilizzo della CPU e fastidiosi rallentamenti, conosciuti come lo stuttering. Advanced Shader Delivery sposta buona parte di questo lavoro nel cloud.
INTERVIEW: Nokia chief technology and AI officer Pallavi Mahajan and Nvidia SVP of telco Ronnie Vasishta told the Mobile World Live Podcast their AI-RAN partnership is showing tangible progress, as they announced close to 20 operators are lined up for lab and commercial trials of the technology.
In an exclusive interview to outline progress of their efforts, Vasishta and Mahajan highlighted the fact it had only been 12 months since the two companies announced a joint AI-RAN partnership, which included a $1 billion investment from Nvidia into the Finnish vendor.
A year on, today (21 October) at Nvidia’s GTC 2026 event in Berlin the duo announced almost 20 operators globally have committed to AI-RAN collaboration, including 10 from EMEA. Mahajan said these operators are at different stages, lined up for both lab and commercial trials.
In 2027 trials are expected from BT Group, Deutsche Telekom and Elisa, with the latter preparing for commercial deployment.
In the US, T-Mobile has completed what was claimed as the world’s first AI-RAN call on a live network, while in France Orange is introducing new voice and intelligence services for enterprises based on the technology.
Speed of light Vasishta told MWL it was hard to overhype development based on the progress it had seen over the past year, and the number of trials and deployment is only set to grow.
“A year ago, or two years ago for sure, I think people would have scoffed at the idea. Nokia talking about operator commercialisation with AI-RAN, I think, that would have been perhaps seen as somewhat sceptical.”
Mahajan concurred, describing the pace of development as occurring “at the speed of light” with the game changer centred on being able to outline the true “value of what AI brings in terms of making RAN efficient” such as significant spectrum efficiency gains.
“In the next few years, the distinction between the networks and computing infrastructure will just blur,” she said, inevitably opening up a host of operator opportunities across applications beyond 5G and 6G.
Vasishta added Nvidia had started on the journey of software-defined RAN eight years ago and the inclusion of Nokia in 2025 had accelerated this dramatically.
“We see all operators around the world are created differently. They service different markets, they have different DNA, but overall, all of them have gravitated towards this concept now of AI RAN.”
With Nvidia’s GTC Berlin event in full swing, the company’s telecoms boss Ronnie Vasishta and Nokia chief technology and AI officer Pallavi Mahajan sit down with the Mobile World Live Podcast in an exclusive interview to reveal the next stage of the pair’s AI-RAN journey, as they team up with European heavyweights to turn networks into distributed intelligence platforms.
RTX Spark is NVIDIA's new local AI-focused Windows PC platform, combining Blackwell RTX graphics and Grace CPU technology into a single processor that brings secure LLMs, high-end creative workflows, and gaming performance to laptops and desktops. With that, NVIDIA positions RTX Spark as a new generation of Windows PCs, with Surface Laptop Ultra as the flagship device.
OEMs are also on board, with RTX Spark laptops launching alongside Microsoft's Surface from brands like HP, Dell, ASUS, and MSI. Our team at Windows Central has followed NVIDIA's efforts closely since its inception and has since gone hands-on with its wave of launch devices. This is everything we know so far about RTX Spark and what we expect to see in the future.
NVIDIA officially entered the Windows PC race this week, and its arrival brings a formidable new competitor to the premium AI PC market. With its RTX Spark platform, NVIDIA is bringing its Grace Arm CPU architecture, Blackwell GPU technology and extensive software ecosystem together in a new generation of Windows laptops. Microsoft’s Surface Laptop Ultra is among the first systems to showcase this collaboration, leveraging NVIDIA’s tech and putting it squarely in competition with Intel, AMD, Qualcomm and even Apple for high-performance local AI and creation-optimized laptops.
For Microsoft, the partnership expands the capabilities of Windows on Arm considerably, particularly for local AI development, content creation and other demanding professional workloads. Starting at $2,599.99, Surface Laptop Ultra is clearly a premium offering, but its combination of processing horsepower, large, unified memory capacity, and premium industrial design gives it an interesting position in the market.
My personal testing suggests NVIDIA and Microsoft have delivered a compelling platform with strong AI throughput, graphics performance and competitive CPU compute. Just as importantly, the Surface Laptop Ultra offers a glimpse of how AI development and local AI agent workflows could become more practical on a portable Windows PC.
NVIDIA RTX Spark brings Grace Blackwell to Windows on Arm
At the heart of Surface Laptop Ultra is NVIDIA’s RTX Spark N1X SoC, combining up to 20 Grace Arm CPU cores with a Blackwell GPU featuring up to 6,144 CUDA cores. Configurations support up to 128GB of unified memory, shared between CPU and GPU. The Surface Laptop Ultra model I tested has this full-fat configuration with an eye-watering $5,899.99 price tag (thanks, memory crunch), though there are lower-cost base configs as noted previously, offering an 18-core CPU with a 5,120-core GPU and 24GB of unified memory.
NVIDIA and Microsoft
Regardless, this architecture is particularly powerful for running on-device AI. Rather than being constrained by the dedicated graphics memory found in conventional laptops with discrete GPUs, RTX Spark can make a much larger pool of memory available to GPU-accelerated applications. This allows larger language models, longer context windows and demanding inference workloads to run locally. It’s similar in design to AMD’s Ryzen AI Max series, aka Strix Halo, in that regard, but with a more potent GPU engine on board.
NVIDIA’s CUDA ecosystem is another important advantage. Developers can leverage familiar tools including TensorRT, PyTorch and llama.cpp, with a base software foundation that also extends into NVIDIA-powered workstations and data center infrastructure.
For organizations building AI applications, this offers a solid development path. Models and workflows can be prototyped locally before moving to larger systems, reducing cloud compute and token expense while allowing sensitive data to remain on-device. (See: Around the corner: Agentic AI PCs that cut token costs.)
Microsoft has also optimized Windows 11 for RTX Spark, with improvements to workload scheduling, power management, memory allocation and application compatibility. These platform-level investments were essential to making NVIDIA’s Arm architecture practical for everyday Windows computing, and I was able to put some of them to the test in the few days I’ve had the machine on hand.
Surface Laptop Ultra: Premium design meets practical function
Microsoft has given RTX Spark an appropriately premium home with this machine. The Surface Laptop Ultra features a 15-inch PixelSense Ultra mini-LED touch display with up to 2,000 nits of claimed peak HDR brightness, a 120Hz refresh rate and excellent potential for creative work requiring high accuracy and wide gamut coverage.
Dave Altavilla
The machine’s aluminum chassis is less than 18 mm thick, and it weighs in at under 4.5 pounds. It’s not an ultraportable per se, but considering the horsepower on board, Microsoft has struck a reasonable balance between portability and performance.
The design is refreshingly understated, with clean lines and rigid aluminum construction. My initial hands-on impressions have been particularly positive, thanks to the keyboard’s tactile response, smooth and responsive haptic touchpad, and bright, high-contrast display.
The larger touchpad should be especially welcome for users navigating complex applications, while the touchscreen adds flexibility for reviewing documents, annotating designs, and interacting directly with creative content.
Connectivity options are also very good, relative to other premium laptops. Microsoft includes three USB-C ports, HDMI, USB-A, an SD card reader and a headphone jack. One USB-C connection features Microsoft’s new magnetic charging mechanism, combining the convenience and safety of a breakaway power connector with the versatility of a standard USB-C port.
Microsoft has also designed the cooling system with large fans and significant thermal capacity, while making the machine’s internal SSD removable and offering good internal serviceability in general. These are practical considerations for professional users and IT departments concerned with reliability, maintenance and long-term ownership.
Battery life and sustained performance under prolonged workloads are important aspects Microsoft focused on for the overall experience, particularly for a machine designed to deliver workstation-class capabilities away from a desk. More on this shortly.
Local AI agents: Moving from inference to action
RTX Spark also supports locally running autonomous AI agents, including one that I tested out called Hermes, which can execute multi-step workflows, access files and interact with applications. Its potential impact spans software development, research, document analysis, business automation and many other disciplines. Hermes provides the agent framework, while supported models leverage RTX Spark’s CUDA-accelerated inference and unified memory.
For businesses, local agents can keep sensitive data on-device and reduce cloud inference costs, provided they’re configured appropriately. However, granting agents access to files, code execution and corporate systems introduces security risks. Microsoft’s Execution Containers and NVIDIA’s OpenShell aim to provide isolation and access controls, though their effectiveness depends on proper enterprise policy implementation.
Hermes running Qwen3.8-27B locally on Surface Laptop Ultra, generating a benchmark report.
Dave Altavilla
To test this capability, I ran Hermes with the Qwen3.8-27B language model locally on the Surface Laptop Ultra. I asked it to extract benchmark charts from an Excel spreadsheet and create a formatted Word report with performance commentary. Hermes autonomously generated and executed Python scripts, processed the spreadsheet and assembled the document in approximately five minutes. Color me impressed.
That’s a respectable turnaround for a task requiring several manual steps. My results demonstrate how local AI agents can streamline reporting and analysis without cloud-hosted model inference. Human review remains essential, but this was a promising demonstration of practical, real-world agentic AI on a Windows laptop.
AI performance: Strong results as expected
My team’s preliminary AI benchmarks highlight the advantages of NVIDIA’s RTX Spark architecture. However, we’re still digging deeper into AI-enabled use cases and performance.
In UL Procyon’s AI Text Generation benchmark using Phi 3.5, a family of lightweight, open-source small language models (SLMs) released by Microsoft, the Surface Laptop Ultra scored 2,703, compared with 2,027 for Lenovo’s Intel Core Ultra X9 388H-powered IdeaPad Pro 5, an advantage of approximately 33%.
Dave Altavilla
The difference was even more substantial in MLPerf’s Flux 2 Klein 4B image generation workload, where the Surface Laptop Ultra delivered 26.97 images per minute versus 9.96 for the Lenovo machine, or roughly 2.7 times the throughput.
These results demonstrate the platform’s potential for accelerating local inference, image generation, agentic workflows and other AI workloads. Actual application performance will depend on model selection, software optimization and available system memory, though NVIDIA does provide a nice memory partitioning tool in the NVIDIA App for Windows.
Content creation, gaming and battery life: Blackwell’s versatility
RTX Spark’s Blackwell GPU delivers impressive graphics performance, extending the Surface Laptop Ultra’s capabilities beyond AI development and everyday creation or productivity tasks.
Dave Altavilla
In 3DMark Steel Nomad Lite, the Surface Laptop Ultra achieved 98.29 FPS, more than double the 46.07 FPS of Lenovo’s Core Ultra X9-powered IdeaPad Pro 5. In the ray-tracing-focused 3DMark Speed Way test, it delivered 30.31 FPS versus 19.72 FPS for the ASUS ROG Flow Z13, powered by AMD’s Ryzen AI Max+ 395 and Radeon 8060S graphics.
Dave Altavilla
Actual gaming performance was similarly strong. In Cyberpunk 2077, the Surface Laptop Ultra averaged 71.05 FPS, ahead of the ROG Flow Z13’s 63.76 FPS. However, the AMD system narrowly led in The Talos Principle 2, delivering 89.5 FPS versus the Surface’s 84.5 FPS at 1080p medium settings.
CPU performance for tasks like 3D rendering also holds up well. In Cinebench 2026, the Surface scored 6,787 in the multi-threaded test, edging out the AMD-powered ROG Flow Z13’s 6,546. Notably, the Surface retained 99% of its multi-threaded performance on battery power as well.
For creative professionals, native Arm applications including Blender, DaVinci Resolve and Adobe Photoshop offer opportunities to leverage RTX Spark’s potent GPU. However, Windows on Arm compatibility remains a consideration. Microsoft’s Prism translation supports many x86 applications, but specialized software, drivers and certain games (like EA anti-cheat-supported titles currently) may still encounter limitations.
Dave Altavilla
Battery endurance was respectable for the Surface Laptop Ultra, at 14 hours and 35 minutes in my PCMark video playback testing, though competing mainstream thin-and-light laptops lasted considerably longer. The Surface Laptop Ultra and RTX Spark operate within a different power envelope, however, more akin to a beefier gaming laptop, rather than a svelte 2 – 3-lb business machine.
Final thoughts: A serious new AI Windows PC competitor
The Surface Laptop Ultra marks an important milestone for NVIDIA’s expansion into Windows PCs and Microsoft’s ambitions for high-performance Arm-based computing.
My initial testing shows the RTX Spark-powered Surface Laptop Ultra delivers exceptionally strong AI acceleration, competitive multi-threaded CPU performance and impressive graphics horsepower. Combined with Microsoft’s premium industrial design, extensive connectivity and I/O options, and Windows platform integration, RTX Spark makes a convincing first impression.
Starting at $2,600, this is a specialized, premium system, and mainstream business users will find more economical alternatives to be sure. However, for developers (even vibe coders), creative professionals and organizations evaluating local AI workflows, the Surface Laptop Ultra offers a compelling combination of performance, beautiful industrial design, portability and local AI capability, especially with its higher-tier memory configurations.
NVIDIA has arrived in the Windows PC market with serious technology, and Microsoft’s Surface Laptop Ultra is an impressive first showcase of what this new partnership can deliver.
Rapid AI adoption left workers cleaning up a flood of errors and low-quality work
Employers around the globe are grappling with the fallout from rushing to adopt fast-changing artificial intelligence tools.
Meta has scaled back plans to axe staff and use more AI agents after the company found employees were spending more and more time cleaning up technical and security errors, Reuters reported. And after thinning its workforce, especially middle managers, in a 2023 efficiency push, the company is expanding its managerial ranks again, LinkedIn posts from workers show.
Mercedes-Benz has signed a definitive production agreement with British self-driving startup Wayve to build its “AI Driver” into future Mercedes vehicles, with integration starting within the next two years.
It’s the first time Wayve’s end-to-end driving AI is going into a production car in the premium segment, and it deepens a relationship that already includes Mercedes investing in Wayve’s $1.5 billion Series D round earlier this year.
As ações da Apple [$AAPL] encerraram o pregão de hoje na Nasdaq cotadas a US$343,99, um novo recorde histórico de fechamento. O recorde anterior havia sido registrado na última sexta-feira (16/10).
Hoje, os papéis da empresa subiram 1,32% e, com isso, o valor de mercado da Apple chegou a US$5,02 trilhões.
Vale notar que o recorde de hoje é apenas o de fechamento. A máxima intradiária (o maior valor atingido durante o pregão) não foi superada nesta sessão, pois permanece a registrada em outro dia.
A Apple segue na segunda posição entre as empresas mais valiosas do mundo. A líder continua sendo a NVIDIA [$NVDA], cujas ações subiram 2,54% hoje, cotadas a US$221,97, com valor de mercado de US$5,36 trilhões. Em terceiro lugar, a uma distância considerável, está a Alphabet [$GOOG], que recuou 1,62%, com ações a US$330,95 e market cap de US$4,047 trilhões.
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