Category robotics

Hexagon leverages industry-leading expertise in measurement technologies, AI and autonomous systems to introduce an advanced humanoid robot to accelerate next-generation autonomy.

Agentic AI is powerful. But without control, it can quickly become a chaotic liability.

As AI systems evolve into more dynamic, generative, and agentic approaches, complexity, cost, and governance challenges multiply.

That’s where an AI gateway comes in.

Think of it like a smart home hub: centrally coordinating devices, enforcing rules, and keeping everything running smoothly.

An AI gateway plays the same role for agentic AI workflows routing tasks, enforcing policies, and reducing infrastructure friction — all in a simple, low-effort way that doesn’t overload your team.

What is an AI gateway?

An AI gateway is a lightweight, centralized layer that sits between your agentic AI applications and the ecosystem of tools, APIs, and infrastructure they rely on.

What it’s not

An AI gateway is not a model, an app, or just another tool in the tech stack. It’s a unifying interface that brings control, abstraction, and agility to your entire AI ecosystem. 

What it unlocks

• Routing and orchestration improve as tasks are automatically directed to the right tools or services based on cost, performance, or policy. Instead of hardwiring logic into every agentic workflow, IT and governance teams stay agile and in control.

• Policy enforcement becomes scalable by applying governance and compliance rules across a web of tools, environments, and teams. What’s usually difficult to standardize in a complex agentic ecosystem becomes consistent and automatic.

• Abstraction and flexibility grows as teams evolve workflows or swap components without rearchitecting systems, adding headcount, or risking costly downtime.

• Operational confidence grows as agentic systems scale with centralized oversight and real-time visibility. Teams can move faster, knowing they’re not trading speed for cost, control, or compliance.

Why AI leaders should care

As agentic AI systems grow, so do the number of tools, models, APIs, and workflows they depend on. Without a unifying layer, every new addition increases complexity and raises the cost to maintain it.

An AI gateway keeps AI cost sprawl in check by:

• Minimizing redundancies
• Reducing tooling overhead
• Improving infrastructure efficiency.

You avoid paying twice (or three times) for capabilities that should be orchestrated, not duplicated.

It also reduces enterprise risk.

By enforcing governance policies and providing oversight across a fragmented yet complex AI stack, an AI gateway ensures consistency as you scale.

Whether you’re adding new agents, adapting to new regulations, or deploying across new environments, it helps standardize compliance, control, and reduce operational gaps.

Because it sits independently from any single model, tool, or cloud provider, an AI gateway gives you the flexibility to evolve your AI systems without getting locked in. You can swap agentic components, optimize for cost or performance, and adapt to change without starting from scratch.

Without an AI gateway, every change becomes rework, and your team ends up drowning in bespoke system maintenance while struggling to manage growing risks.

How AI gateways reduce cost, risk, and friction

Here are just a few examples of how an AI gateway streamlines complexity as your systems scale.

Swapping an LLM for a cost-efficient one

Without a gateway:
Teams have to manually rewire workflows, risking broken chains, regressions, and delays. What should be a cost-saving move ends up burning time, resources, and budget.

With a gateway:
A simple routing update handles the change. You can swap out an LLM agent or update an agentic flow without rearchitecting — so cost savings don’t come with hidden costs.

Responding to a regulation change

Without a gateway:
Every agent and its tool stack must be assessed and updated manually, creating delays and compliance gaps.

With a gateway:
You apply the policy once, and it’s enforced consistently across all tools and environments.

Adding a new tool to an agentic chain

Without a gateway:
Integrations are brittle and often lead to downtime or duplicated effort.

With a gateway:
Plug-and-play orchestration allows you to test and introduce new tools quickly while maintaining consistent governance and reliability.

What breaks without an AI gateway

The risks compound quickly. As your AI systems evolve, so do the dependencies, costs, and failure points. Without a unifying layer, every new tool, workflow, or requirement adds overhead, complexity, and risk.

Skyrocketing infrastructure costs

Redundant tools, compute inefficiencies, and custom integrations drive up operating expenses (OPEX) and capital expenses (CAPEX) at an unsustainable pace.

OPEX drivers:

• Redundant workflows repeatedly calling external APIs or LLMs
  
• Increased FTE hours spent on manual tracing, monitoring, or stitching together tools
  
• API and SaaS sprawl as siloed tools each require separate contracts and maintenance
  

CAPEX drivers:

• Custom infrastructure built per use case, like duplicative vector databases or tool registries
  
• One-off governance tooling developed app-by-app
  
• Underused hardware or software licenses with no shared orchestration layer to optimize usage
  

Security and governance blind spots

Without a centralized layer, there’s no consistent way to enforce policies, monitor usage, or trace agent behavior, making governance fragmented and incomplete.

Rigid, brittle systems

Tool swaps or workflow changes become high-effort, high-risk projects. Even small updates can require full rework, slowing innovation and adding operational drag.

Why this matters now

The age of agentic AI is arriving faster than most teams are ready for. 

What started as experimentation is quickly shifting to production, moving from linear pipelines to dynamic, autonomous systems. But many organizations are layering this complexity onto brittle, point-to-point architectures that can’t keep up.

An AI gateway is not a future luxury. It is what prevents today’s agentic experiments from becoming tomorrow’s operational nightmares when autonomous workflows multiply, new regulations emerge, or tool sprawl explodes.

The longer you wait, the harder it becomes to retrofit abstraction, control, and agility into a system that was not built for agents. An AI gateway lays the foundation now so you can scale agentic AI with speed, security, and confidence later.

Common misconceptions about AI gateways

If AI gateways feel unfamiliar or confusing, you’re not alone. Let’s clear up a few of the most common misconceptions.

“Our stack already covers orchestration and governance.”

Unless you have a unified layer that orchestrates, provisions, swaps, and governs all your AI agents and integrations — without vendor lock-in — you don’t have a true AI gateway. Most tools only simulate fragments of this.

“This is only for advanced, multi-agent systems.”

Even simple single-agent systems benefit. Gateways eliminate technical debt before it multiplies.

“Isn’t this just more overhead?”

No. Gateways eliminate overhead by reducing integration work, unifying control, and minimizing compliance risk, while also helping you optimize for cost across tools, agents, and environments.

“Won’t this lock us in?”

A true gateway is vendor-agnostic. It actually protects you from deeper tool lock-in by decoupling your apps from specific APIs.

Get ahead of AI complexity with the right foundation

If agentic AI is on your roadmap, now’s the time to lay the foundation.

An AI gateway gives you the control, flexibility, and cost discipline to scale with confidence, without the architectural growing pains.

Want to scale agentic AI without spiraling cost or risk?

 Download The enterprise guide to agentic AI ebook for a practical roadmap to scale securely, cost-effectively, and with full control from the start.

The post Why your agentic AI will fail without an AI gateway appeared first on DataRobot.

The loss of a limb following an injury, accident or disease can greatly reduce quality of life, making it harder for people to engage in daily activities. Yet recent technological advances have opened new exciting possibilities for the development of more comfortable, smarter and intuitive prosthetic limbs, which could allow users to easily complete a wider range of tasks.

A team of engineers at Singapore University of Technology and Design has created a truly unique robot—one that can roll around like a drum, then take off and fly like a spinning wheel. In their paper published in The International Journal of Robotics Research, the group describes their goals in developing the robot and how they were achieved, along with a description of how it works.

Explore the latest Gemini 2.5 model updates with enhanced performance and accuracy: Gemini 2.5 Pro now stable, Flash generally available, and the new Flash-Lite in preview.

Gemini 2.5 Flash and Pro are now generally available, and we’re introducing 2.5 Flash-Lite, our most cost-efficient and fastest 2.5 model yet.

Bees, ants and termites don't need blueprints. They may have queens, but none of these species breed architects or construction managers. Each insect worker, or drone, simply responds to cues like warmth or the presence or absence of building material. Unlike human manufacturing, the grand design emerges simply from the collective action of the drones—no central planning required.

Averna has developed a procedure for automating battery inspection for one of its customers. The fact that potential errors are extremely varied increases the complexity of the inspection process.

Professor Peng Lu and his team from the Department of Mechanical Engineering of Faculty of Engineering at the University of Hong Kong (HKU), have achieved a milestone in aerial manipulation technology. Their innovative Aerial Elephant Trunk (AET), a novel aerial continuum manipulator, has demonstrated unparalleled capability in performing complex aerial manipulation tasks, marking a significant leap forward for the development of the low-altitude economy.

Much like an app store for robotic intelligence, the Neuraverse allows robots to share and continuously evolve their skills: from welding and assembly to household tasks like ironing.

A new, densely annotated 3D-text dataset called 3D-GRAND can help train embodied AI, like household robots, to connect language to 3D spaces. The study, led by University of Michigan researchers, was presented at the Computer Vision and Pattern Recognition (CVPR) Conference in Nashville, Tennessee on June 15, and published on the arXiv preprint server.

Researchers have created a revolutionary robotic skin that brings machines closer to human-like touch. Made from a flexible, low-cost gel material, this skin transforms the entire surface of a robotic hand into a sensitive, intelligent sensor. Unlike traditional robotic skins that rely on a patchwork of different sensors, this material can detect pressure, temperature, pain, and even distinguish multiple contact points all at once.

In the irony of ironies, Google – one of ChatGPT’s fiercest competitors – has agreed to provide cloud computing services to its nemesis.

Observes lead writer Kenrick Cai: The deal “underscores how massive computing demands to train and deploy AI models are reshaping the competitive dynamics in AI.”

Google competes head-to-head against ChatGPT with its own chatbot, Google Pro 2.5.

In other news and analysis on AI writing:

*ChatGPT Controls 80% of the AI Market: Despite their best efforts, competitors to ChatGPT are unable to approach the chatbot’s influence worldwide.

Observes writer Jose Antonio Lanz: “ChatGPT attracts more traffic than the next nine AI tools combined, with 5.5 billion visits crushing Gemini and Claude.

“ChatGPT has become the default AI assistant for hundreds of millions of users worldwide.”

*Is AI Friend or Foe?: Local News Outlets About to Find Out: A new study finds that local news outlets are still wondering if AI represents a second chance for them – or their final death knell.

Observes study researcher Mark Caro: “Many people who practice or care about journalism fear that generative AI, with its ability to create content with little human
involvement, could be the final nail in the local
news coffin.”

In contrast, AI like ChatGPT “is only the latest in a long line of technological advancements that, when used correctly, should make work more efficient and easier.”

We’ll all know soon enough how things shake-out.

*AI Drives Major Layoff at News Outlet: AI has made news magazine Business Insider so much more efficient, it was able to layoff 21% of its staff, according to the magazine’s CEO Barbara Peng.

Yay?

Observes writer Mike Kaput: “In a company-wide memo, CEO Barbara Peng made it crystal clear: AI was central to their strategic pivot.

“More than 70% of Business Insider employees are already using Enterprise ChatGPT regularly.

“The goal? Full adoption.”

“Peng framed the layoffs not as an unfortunate byproduct of AI usage, but as part of a broader vision to make the company leaner, faster, and more future-proof.”

*Bleeding Edge Text-to-Voice Provider Out With a Major Upgrade: Eleven Labs – a text-to-voice provider considered by many to be among the very best – is out with a major upgrade.

Observes writer Web Wright: “The new model can exhibit a wide range of emotions and subtle communicative quirks — like sighs, laughter, and whispering — making its speech more humanlike than the company’s previous models.”

*The Gloves Are Off: We’re Looking to Replace You With AI: San Francisco start-up Mechanize minces no words when summing up its raison d’etre: It’s looking to automate white-collar jobs with AI as fast as possible.

In fact, Mechanize’s ultimate dream is to so fully automate the economy, humans at workplaces will become superfluous, according to company co-founder Tamay Besiroglu.

One thing is certain: The sweet-talking days when AI was simply going to be our AI buddy collaborator (last year) are long gone.

*The ‘Post-Search Era’ for Publishers Has Arrived: Google’s AI-powered search is so successfully eliminating the need to visit news sites for information, some publishers are beginning to talk of a ‘post-search era’ for online journalism.

Observes lead writer Isabella Simonetti: “Traffic from organic search to HuffPost’s desktop and mobile websites fell by just over half in the past three years — and by nearly that much at the Washington Post.”

Moreover, “at a companywide meeting earlier this year, Nicholas Thompson, chief executive of the Atlantic, said the publication should assume traffic from Google would drop toward zero and the company needed to evolve its business model,” Simonetti adds.

“Generative AI is now rewiring how the internet is used altogether.”

*Sucking Wind: Apple Still Gasping to Get Current on AI: Despite efforts to pretty-up its AI image with promises of a powerful AI future, Apple failed to convince coders at its annual developers contest that it has AI game, according to writer Dan Gallagher.

To be fair, Apple deliberately strove to set expectations relatively low at the conference, after many of its AI dream features promised last year never materialized.

Observes Gallagher: “Apple no doubt wanted to avoid the trap it fell into last year, when it introduced its Apple Intelligence service to great hype only to have its later launch and subsequent updates fall short of promises.”

*Oh Right – AI Agents Can Get Hacked, Too: A new study finds that AI agents made by Microsoft – which can accomplish complex missions featuring a number of independent actions and decisions – can be hacked.

Observes writer Sharon Goldman: “In the case of Microsoft 365 Copilot, the vulnerability lets a hacker trigger an attack simply by sending an email to a user, with no phishing or malware needed.

“Instead, the exploit uses a series of clever techniques to turn the AI assistant against itself.”

The discovery throws cold water on the idyllic dreams of an AI agent future, when a writer, for example, could theoretically program an AI agent to research, write – and continually update – an article.

Apparently, such an agent might be maliciously hacked to say include inaccurate information in that article, feature false quotes — and more.

*AI BIG PICTURE: AI ‘Companions for Seniors’ Now a Thing: In an unexpected twist, a Delaware start-up is out with a new service that offers AI friends for seniors.

For $20/month, seniors can simply pick-up a phone and start talking with an AI chatbot that promises warm, engaging conversation.

Observes company spokesperson Amanda Garcia: “The newly launched phone-based option works with any U.S. landline or mobile number.”

Meanwhile, seniors who prefer to interact via text chat can sign-up for a text-based account for $10/month.

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–Joe Dysart is editor of RobotWritersAI.com and a tech journalist with 20+ years experience. His work has appeared in 150+ publications, including The New York Times and the Financial Times of London.

The post Key Rival Lends ChatGPT a Hand appeared first on Robot Writers AI.

AI has helped astronomers crack open some of the universe s best-kept secrets by analyzing massive datasets about black holes. Using over 12 million simulations powered by high-throughput computing, scientists discovered that the Milky Way's central black hole is spinning at nearly maximum speed. Not only did this redefine theories about black hole behavior, but it also showed that the emission is driven by hot electrons in the disk, not jets, challenging long-standing models.

UC San Diego engineers have created a passive evaporative cooling membrane that could dramatically slash energy use in data centers. As demand for AI and cloud computing soars, traditional cooling systems struggle to keep up efficiently. This innovative fiber membrane uses capillary action to evaporate liquid and draw heat away without fans or pumps. It performs with record-breaking heat flux and is stable under high-stress operation.