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Google Plans A Future Where Robots Think For Themselves
Google is helping robots better understand how to be helpful to humans, and the results are encouraging!
Unknown to many of its fanbase, search giant Google has been developing its own semi-secret research laboratory for over a decade. The project is known as X Developments and focuses on exciting projects such as the recent Everyday Robots collaboration.
The project emphasizes the software side of robotics, aiming to make the technology helpful to humans by optimizing robots for tasks that include finding, fetching, and sorting items, as well as training bots to be awesome at ping-pong or catching racquetballs.
Google’s latest milestone is the “Pathways Language Model,” a software solution that gives the company’s robots a better understanding of the world, helping them respond more accurately and efficiently to human requests. So far, the robot workers at Google have been set to work on less-than-glamorous tasks such as trash sorting, with the aim that eventually, they will be able to take on tasks and teach themselves on the fly. Research into seemingly useless tasks like ping-pong might seem frivolous, but these operations require speed and precision, so they help engineers tune their robot sidekicks for future requirements.
Google’s emphasis on robotic precision means that the company is unlikely to release a product for the general public any time soon. Their stance stands in sharp contrast to rival Amazon, which has already offered a product to market named Astro (albeit invite-only) — a $999 robot that seems to offer little more than basic Alexa functionality on wheels.
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“Google tries to be a company that provides access to information, helping people with tasks in their daily lives, you could imagine a ton of overlap between Google’s overarching mission and what we’re doing in terms of more concrete goals. I think we’re really at the level of providing capabilities, and trying to understand what capabilities we can provide,” says Vincent Vanhoucke, Google Research Robotics Lead.
Don’t expect to see a Google-themed robot appearing anytime soon, but keep an eye out for the latest developments from X Developments, as even the company’s homepage points to an exciting future for human / robot partnerships!
News
NVIDIA Puts GPT-5.5 Codex In Hands Of 10,000 Staff
The chipmaker has significantly expanded OpenAI’s latest model across teams from engineering to HR under tight internal controls.
NVIDIA has started rolling out OpenAI’s GPT-5.5 model through the Codex coding agent to more than 10,000 employees, extending the tool well beyond software teams and into core business functions.
The deployment covers engineering, product, legal, marketing, finance, sales, HR, operations and developer programs. Staff are using Codex for coding, internal research and routine knowledge work as companies test whether AI agents can move from demos to daily use.
GPT-5.5 is running on NVIDIA’s GB200 NVL72 rack-scale systems, linking OpenAI’s newest model directly to the chipmaker’s latest infrastructure push. NVIDIA said the systems cut cost per million tokens by 35 times and raise token output per second per megawatt by 50 times versus earlier generations.
Inside the company, it says the effects are immediate. Debugging work that once took days is being finished in hours and experiments across large codebases that used to stretch over weeks are now handled overnight. Teams are also building features from natural-language prompts with fewer failed runs.
In a company-wide note urging staff to adopt the tool, CEO Jensen Huang wrote: “Let’s jump to lightspeed. Welcome to the age of AI.”
Security remains central to the rollout. Codex can connect through Secure Shell to approved cloud virtual machines, allowing agents to work with company data without moving it outside approved environments. NVIDIA said it assigned cloud VMs to employees so agents run in isolated sandboxes with full audit trails.
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The company added that the setup uses a zero-data-retention policy. Access to production systems is read-only through command-line tools and internal automation layers.
The move also highlights NVIDIA’s long relationship with OpenAI. NVIDIA said the partnership began in 2016, when Huang personally delivered the first DGX-1 AI supercomputer to OpenAI’s San Francisco office.
The two companies have since worked across hardware and model deployment. NVIDIA also said OpenAI plans to deploy more than 10 gigawatts of NVIDIA systems for future AI infrastructure.
For Gulf markets pouring money into sovereign AI and enterprise automation, the signal is clear: internal AI agents are moving from pilot phase to standard tooling.
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