Category robots

But Experimental Alternatives Have Problems

While ChatGPT-4o – the default AI engine for writing, research and similar work – remains formidable, some problems are cropping up with experimental models.

Specifically, ChatGPT-o3, ChatGPT-o4 mini and ChatGPT-o4 mini high – which use advanced reasoning – ‘make-up-facts’ more often when responding to questions from users.

Bottom line: If you want to be sure ChatGPT sticks-to-the-facts when auto-writing your emails and other text, there’s a prompt you can use that eliminates such hallucinations.

For the prompt, simply check-out the free sample read of “Auto Writing World-Class Emails With ChatGPT,” by Joe Dysart, available on Amazon.

Once you’re on the Amazon book page, click the free sample read button, scroll to Chapter 6 and grab the free prompt there that deep-sixes hallucinations.

In other news and analysis on AI writing:

*Mark Zuckerberg Releases ChatGPT-Competitor: Facebook inventor Mark Zuckerberg has released a direct competitor to ChatGPT, dubbed ‘Meta AI.’

While Zuckerberg – CEO of Facebook parent company Meta – has already infused many of his company’s apps with artificial intelligence, this is the first time he’s going in a head-to-head competition against today’s major chatbot competitors with a stand-alone AI chatbot.

Designed with the look and feel of ChatGPT, Meta AI “enables users to have natural, back-and-forth voice conversations with AI, edit and generate images — and discover new use cases through a curated Discover feed featuring prompts and ideas shared by the community,” according to writer Carl Franzen.

*ChatGPT: Matching the Right AI Engine for Your Task: ChatGPT runs on a number of different AI engines these days – each optimized for specific tasks.

Here’s the breakdown:

–Everyday writing: ChatGPT-4o is the go-to alternative for everyday writing tasks and heavily tried, true and tested.

–Advanced Creative Writing: ChatGPT-4.5 is billed as an advanced creative writing tool – especially for users looking for AI with advanced emotional intelligence. The only downside: If you’re on ChatGPT Plus, you can only send 20 messages to ChatGPT-4.5 each month.

–Advanced Reasoning: ChatGPT-3o, ChatGPT-o4 mini and ChatGPT-o4 mini high

*Google Rolls-Out AI for the ’Under-13’ Crowd: In a controversial move, Google is allowing kids to access its Gemini Chatbot under their parent-managed Google accounts.

Observes writer Natasha Singer: “Google acknowledged some risks in its email to families this week, alerting parents that Gemini can make mistakes and suggesting they help your child think critically about the chatbot.”

You mean help your five-year-old think critically about what an AI chatbot – which can be interacted with via voice conversation – says to your five-year-old when you might not be around?

Sure. That’ll work.

*ChatGPT-Maker Pitches Itself as the Solution for Democracies: In another sign that much of the free world may run on its own version of AI, ChatGPT’s maker OpenAI is marketing itself as the solution for democracies.

Observes an OpenAI blog post: “This is a moment when we need to act to support countries around the world that would prefer to build on democratic AI rails, and provide a clear alternative to authoritarian versions of AI that would deploy it to consolidate power.”

*Study: AI Writer/Editor Grammarly Boosts Productivity: Grammarly is out with a new study revealing that customers using its AI tools experience a 17% boost in productivity.

The reason: Customer service agents that used Grammarly in their writing interactions with customers found that their writing was clearer, more mistake-free, sounded more on brand – and was easier to finish, according to writer Esther Shittu.

Grammarly was able to prove the new efficiencies by putting its AI writer/editor to an A/B test at companies, in which half of employees in the test had access to Grammarly — while the other half did not.

*Top AI Writing Tools for Students: The Houston Press has come up with its list of preferred tools for student writing.

Along with general-use tools like Grammarly and Rytr, Houston Press also likes the following for academic-focused writing:

–StudyPro: All-in-one academic platform specializing in research, writing, and editing

–Paperpal: Good for research-based academic writing and journal formatting

–Samwell.ai: Good for guided essay planning and structured development

–Quarkle.ai: Good for idea brainstorming and fast topic exploration

*AI News Summarizer Promises to Bring Readers to News Outlets: Particle, a new Web app that offers AI-powered summaries of breaking news, is promising to bring readers to the news outlets that are the sources of those summaries.

Observes writer Sarah Perez: Particle “highlights the news outlets covering a story by sharing links to their stories directly alongside its AI summaries.

“In early tests on mobile, the company found that readers were clicking through to the publishers’ sites via these links, leading Particle to begin partnering with specific publishers like Reuters, Fortune, and the AFP to display their links more prominently.”

*Many Journalists Remain Fearful of AI: Years after being cast as an ‘AI collaboration buddy,’ AI-automated writing and similar apps available with AI still leave many journalists fearing for their jobs.

Specifically, a new study finds that 57.2% of journalists believe AI could displace even more jobs in coming years.

Even so, the study revealed a silver lining: “Approximately 50% believe that AI could create new roles within journalism, particularly in managing and overseeing AI tools,” according to writer Chris Price.

*AI Big Picture: People Are Falling in Love With AI Companions: In a world often starved for intimacy, AI companions are stepping up as solutions – often with unintended consequences.

This riveting video from “60 Minutes Australia” finds that growing numbers of people are coupling with AI, insisting that their AI companions are more trustworthy than many humans.

There’s also a darkside to the trend: One male teenager committed suicide in an attempt to be closer to his “AI lover.”

Share a Link:  Please consider sharing a link to https://RobotWritersAI.com from your blog, social media post, publication or emails. More links leading to RobotWritersAI.com helps everyone interested in AI-generated writing.

–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 ChatGPT’s Workhorse AI Engine Still Solid Choice appeared first on Robot Writers AI.

Phase-change actuation has been revived for the era of untethered, electrically driven soft robots. Our team at the University of Coimbra have developed a phase transition soft actuator designed to power electric soft robots that require high force and precision. Our innovation leverages the liquid-to-gas phase transition of water to generate mechanical motion in a way that is simple, scalable, and remarkably powerful.

A joint research team from Seoul National University and Harvard University has developed a next-generation swarm robot system inspired by nature—capable of movement, exploration, transport, and cooperation, all without the need for precise sensors or centralized control.

435 AMRs are now live at Chery's Dalian factory, transforming internal logistics and setting a new benchmark for scalable, intelligent automation in the industry.

Claire chatted to Emma Hart from Edinburgh Napier University about algorithms that ‘evolve’ better robot designs and control systems.

Emma Hart is a computer scientist working in the field of evolutionary computation. Her work takes inspiration from the natural world, in particular biological evolution, and uses this to develop algorithms that ‘evolve’  both the design and control systems of a robot, customised  to a specific application. She was elected as a Fellow of the Royal Society of Edinburgh in 2022, and was awarded the ACM SIGEVO Award for Outstanding Contribution to Evolutionary Computation in 2023. She was invited to give a TED Talk on her work in 2021 that has over 1.8 million views.

Researchers developed FaceAge, an AI tool that calculate's a patient biological age from a photo of their face. In a new study, the researchers tied FaceAge results to health outcomes in people with cancer: When FaceAge estimated a younger age than a cancer patient's chronological age, the patient did significantly better after cancer treatment, whereas patients with older FaceAge estimates had worse survival outcomes.

Engineers developed a ping-pong-playing robot that quickly estimates the speed and trajectory of an incoming ball and precisely hits it to a desired location on the table.

Brown University researchers have developed an artificial intelligence model that can generate movement in robots and animated figures in much the same way that AI models like ChatGPT generate text.

A research team from AMOLF in Amsterdam has created a soft robot that walks, hops, and swims—all without a brain, electronics, or AI. Just soft tubes, air, and some clever physics.

You’re expected to support next-gen AI on infrastructure that was never designed for it. 

In highly regulated industries like government, financial services, and healthcare,  IT teams face growing pressure to drive innovation while staying compliant.  

But traditional systems can’t keep up with  the speed, scale, or complexity that generative and agentic AI demand. 

The result is a widening gap between business expectations and what existing infrastructure can support.  

This creates a two-fold challenge: 

1. Ensuring continuous security and compliance across production systems.
   
2. Delivering AI fast enough to meet business needs, without blowing through time, cost, or resources.  

And for most teams, starting from scratch with open source tooling isn’t realistic.  

What’s needed is a composable, integrated AI foundation that works across environments, simplifies operations, and gives IT teams the tools and shortcuts to deliver outcomes fast, without compromising security or governance.

Why AI stalls in high-security environments

AI initiatives often lose momentum — or never reach production — due to barriers like:

• Procurement and integration delays: Acquiring and deploying new tools takes too long, stalling adoption and impact.
  
• Disconnected infrastructure: Disparate and siloed systems block access to the right data and make it hard to design a scalable, resilient AI stack.
  
• Operational complexity: IT teams spend more time maintaining tools than enabling data science.
  
• Rigid security and compliance demands: Every new component requires vetting, testing, and regulatory approval when AI demands quick iteration.
  
• Poor observability and blind spots: Limited visibility leads to rework in the short term and audit delays down the line. 

These challenges are deeply interconnected. Patchwork fixes won’t address them.

Delivering outcomes at scale requires a platform that simplifies infrastructure, embeds security and governance,  and gives IT teams the tools and control they need to move fast, without compromising trust. 

Validated by Nutanix. Built for regulated environments.

IT leaders need more than a patchwork of tools; they need a secure, scalable platform that works right out of the box.

That’s exactly what we’ve built with Nutanix.

We’re proud to be recognized as Nutanix’s 2025 Americas Technology Alliance Partner of the Year — a reflection of our shared focus on simplifying agentic AI for highly regulated, on-prem environments.

This recognition highlights the strength of our joint solution: a fully validated, enterprise-grade AI platform that runs securely on Nutanix infrastructure. It enables rapid deployment, built-in governance, and full-stack integration, helping teams accelerate adoption without compromising compliance or control.

 Simplifying agentic AI delivery on-prem

Current tools and infrastructure weren’t built for the speed, scale, or security that AI demands — especially in highly regulated, on-prem environments.

DataRobot and Nutanix remove the friction with a fully integrated platform that simplifies setup, secures access to the latest models, and embeds observability and governance from the start.

Together, we offer a validated AI stack purpose-built for high-security on-prem and air-gapped environments. This end-to-end solution gives IT leaders the speed, and compliance needed to deliver AI value within budget, without sacrificing control. 

It’s fast to set up, easy to manage, and built to support secure, governed AI from development through deployment. 

Nutanix: Build a scalable, secure foundation

• Setup and scale securely: Deploy Nutanix Enterprise AI on CNCF-certified Kubernetes — scalable, cost-efficient, and ready for high-security workloads.
  
• Simplify access to the latest models: Deploy open-source LLMs, including NVIDIA NIM, with streamlined  model selection and management.
  
• Manage and protect every endpoint: Stand up resilient endpoints with built-in security to test and run models safely.
  

DataRobot: Deliver business-ready agentic AI apps

• Build enterprise-grade AI apps: Use prebuilt templates or create custom apps for high-security use cases within a flexible, production-ready development environment.
  
• Ensure trust and compliance: Apply built-in guardrails and generate compliance documentation to support audit readiness.
  
• Deploy and govern at scale: Move apps to production with continuous monitoring and full governance oversight.

DataRobot delivers mission-critical AI apps for federal agencies

Federal agencies can’t afford disruption. That’s why DataRobot delivers mission-critical AI apps designed to integrate with existing systems and deploy where your data lives, so you can move fast, stay compliant, and drive mission outcomes without overhauling your infrastructure.

Our AI applications tackle a wide range of critical use cases, including:

• Budget insight and contract optimization: Identify underutilized funds and model future resource needs to drive smarter, faster budget decisions.
  
• Fraud, waste, and abuse surveillance: Detect anomalies early with continuous data monitoring and automated compliance alerts.
  
• Talent management and force readiness: Optimize recruitment, retention, and training investments to maintain a mission-ready workforce.
  
• Operational Efficiency and Predictive Maintenance: Streamline procurement and predict equipment failures to boost fleet availability and lower costs.

Secure on-prem AI without compromise

For IT leaders in regulated industries, AI success often means tough trade-offs: speed vs. control, innovation vs. compliance, usability vs. security, budget overruns vs. mission outcomes. 

In sectors like public, healthcare, and financial services, the challenge is meeting every requirement — without slowing down progress.

To move from AI ambition to real results, ask yourself:

• Is your infrastructure fast, secure, and flexible enough to adapt?
  
• Are security and compliance controls built in and simple to use?
  
• Do your tools and apps enable teams to deliver on business needs?

This is the new operational baseline for secure AI delivery in highly regulated environments, and it’s exactly what Nutanix and DataRobot make possible.

With this platform, you can deploy AI securely, efficiently, and without compromise — turning ambition into measurable outcomes.

Book a demo with a DataRobot expert and explore what’s possible for leveraging the latest AI advances in your on-prem data environment.

The post Simplifying secure on-prem AI with Nutanix and DataRobot appeared first on DataRobot.

It's easy to take joint mobility for granted. Without thinking, it's simple enough to turn the pages of a book or bend to stretch out a sore muscle. Designers don't have the same luxury. When building a joint, be it for a robot or wrist brace, designers seek customizability across all degrees of freedom but are often restricted by their versatility to adapt to different use contexts.

Researchers have developed a more efficient chip as an antidote to the vast amounts of electricity consumed by large-language-model artificial intelligence applications like Gemini and GPT-4.

A team of researchers has unveiled a cutting-edge Amphibious Robotic Dog capable of roving across both land and water with remarkable efficiency.

An edible robot leverages a combination of biodegradable fuel and surface tension to zip around the water's surface, creating a safe -- and nutritious -- alternative to environmental monitoring devices made from artificial polymers and electronics.

What makes people think an AI system is creative? New research shows that it depends on how much they see of the creative act. The findings have implications for how we research and design creative AI systems, and they also raise fundamental questions about how we perceive creativity in other people.