Researchers have developed a technology that lets a user move a small robot by bending and straightening a finger. The user can also pick up and move objects while checking the images and contact information that the robot sends back.

A recent segment on The Daily Show where Jon Stewart Unpacks AI’s Dubious Promise of a “Better Future” exposed a glaring blind spot in executive boardrooms across the globe. In the broadcast, Stewart dissects the White House AI summit, where […]

The post The One Job Silicon Valley Forgot to Invent: Why Every Enterprise Needs a Chief AI Consequence Officer (CACO) appeared first on Techspective: A Unique Perspective on Technology.

Highly reflective metallic surfaces are among the most challenging inspection targets in machine vision. Reflections obscure details, defects often only become visible from certain angles, and the quality of manual visual inspections fluctuates throughout the workday.

Oxford physicists have recreated a bizarre quantum effect in which a particle responds to a magnetic field without ever traveling through it. Using a hybrid quantum computer, they demonstrated how introducing a simulated magnetic flux could completely halt a particle's movement through quantum interference. The experiment brings a decades-old prediction into a new setting where matter and quantum fields influence one another.

Scientists have uncovered a surprising hidden ability of light that allows it to develop spinning, twisting behavior as it travels through empty space, without special lenses, mirrors, or materials. Researchers discovered that light’s internal geometry can naturally produce left- and right-handed patterns, challenging long-standing assumptions about how light behaves. By carefully arranging a beam’s structure, scientists can control where and how these spinning patterns emerge, unlocking a new way to manipulate light.

This article looks at where those areas tend to be, what the international register of certified robots actually contains, and the five questions a plant should settle before a robot goes in.

By Wai-keung Fung, Cardiff Metropolitan University

At the recent World Humanoid Robot Games 2026 in Beijing, robots sprinted, boxed, played football and tackled tasks inspired by factories, restaurants and emergency situations. The robot Tiangong Ultra even completed the 100 metres in 8.64 seconds, quicker than Usain Bolt’s 9.58-second world record.

But if we really want to know whether humanoid robots are ready for everyday life, a far less glamorous challenge may tell us more: doing the laundry. Can a robot take a crumpled T-shirt from a laundry basket, work out which way round it is, fold it neatly and recover when the sleeve slips from its hand?

No robot system can yet reliably handle the whole laundry process, from carrying a basket to the washing machine and sorting clothes for different programmes to taking them out, hanging them to dry, folding and ironing them. Even folding remains a challenge: robots need to cope with clothes of different shapes, sizes, materials and levels of creasing.

Running fast is difficult, of course. A humanoid has to coordinate many joints, keep its balance and generate powerful movements without falling over. The task itself, however, is fairly clear. The robot knows where to go, the track is predictable and the finish line does not suddenly change shape.

Laundry is a very different problem. A shirt may be inside out. One sleeve may be hidden underneath another garment. A pair of trousers may be twisted around a towel. Fabric is also soft and constantly changing shape. Pick up one corner of a T-shirt and the rest of it moves.

Humans deal with this without giving it much thought. We shake a shirt out, notice where the sleeves are, feel when the fabric slips and adjust our grip almost automatically. For a robot, every one of those little actions is a problem to solve. This is why an everyday chore can reveal more about robot intelligence than a spectacular athletic feat.

A useful household robot cannot simply replay the same movement again and again. It has to notice when reality is different from what it expected and adapt. That’s important to consider because humanoid robots are increasingly discussed as future helpers in homes and care settings, as well as factories and warehouses.

A factory production line can often be arranged so that parts arrive in predictable positions. A family home is not like that: clothes, toys and furniture move around constantly, while people, children and pets make the environment even less predictable.

Why one robot cannot simply copy another

There is another difficulty. Once one robot learns how to fold a shirt, it might seem obvious that we should simply transfer that skill to every other robot. Unfortunately, physical skills do not work like an app that can be installed on any machine.

Imagine a specialist laundry robot with rigid arms, overhead cameras and grippers designed specifically for fabric. A humanoid may have cameras in its head, five-fingered hands and different joints and balance constraints. The same movement could therefore produce a very different result.

A fixed robot arm can reach forward without worrying about falling over. A humanoid may have to move its hips, legs and feet just to keep itself stable while reaching across a table.

Sensors are important too. One robot may have sensitive touch sensors in its fingers. Another may rely mainly on cameras.

Some knowledge can still transfer. One robot can teach another something about what a shirt looks like, where its shoulders are likely to be, what a good fold looks like or how to recognise when a sleeve is trapped underneath. The receiving robot still has to work out how to carry out those ideas with its own hands, joints, cameras and body.

Research projects such as Open X-Embodiment are exploring exactly this problem by pooling experience from many different robots. The project has brought together more than one million real robot trajectories from 22 different robot types. The hope is that robots can learn useful patterns from one another rather than starting from zero every time.

What should count as progress?

The Humanoid Robot Games are valuable because they make robotics visible and show how quickly the technology is moving.

We should simply be careful about what those demonstrations prove. For robots intended to live and work alongside us, better questions might be: can the robot deal with an unfamiliar object? Can it notice that it has made a mistake and recover without human intervention? How long can it keep working before someone has to step in?

These measures are unlikely to produce viral videos. They are, however, much closer to the abilities that will determine whether humanoid robots become genuinely useful.

A robot that can run 100 metres faster than the human world record time is impressive. A robot that can take a messy basket of laundry, sort it, fold it and recognise when things have gone wrong may tell us far more about whether general purpose robot intelligence has really arrived.

The most important race for humanoid robots may not be against the clock. It may be against the laundry pile.

Wai-keung Fung, Senior Lecturer in Electronics Robotics & Control Engineering, Cardiff Metropolitan University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Virtual Dead Heat

A new study finds U.S. AI is only 3% better than top alternatives from China.

That ranking comes from Bloomberg Analyst Robert Lea, who says AI from China shrank the gap to 3% with the release of DeepSeek V4.1 Flash.

Observes the Business Times: “China’s ascent is a result of deepening AI expertise and its researchers’ ability to optimize their models for domestic hardware.”

In other news and analysis on AI writing:

*Chinese AI Phenom DeepSeek on Track for $12 Billion in New Funding: Nearly- as-good-as-U.S.-AI -maker DeepSeek appears certain to raise at least another $12 billion as it readies to launch as an IPO in early 2027.

DeepSeek has been a hit with many U.S. firms, which prefer Open Source AI that often costs pennies-on-the-dollar compared to AI from OpenAI, Anthropic, Google and the like.

Observes writer Cris Tolomia: “At investor meetings this year, DeepSeek founder Liang Wenfeng committed to keeping DeepSeek’s AI models open and said the company’s overarching aim is advancing toward artificial general intelligence.”

*ChatGPT-6 – OpenAI’s Smartest Model – Now Available for Free Users: People who don’t pay a cent for AI can still get a taste of OpenAI’s smartest AI for free.

Observes the OpenAI Blog: “We’re bringing that next generation of intelligence to more people with a new GPT‑6 model built for more than 1.2 billion people who use ChatGPT each week.”

*ChatGPT-6 Answers Get Prettier: Look for More Graphics, Photos, Buttons, Forms, Charts and Interactive Experiences: Apparently, it’s not enough for bleeding edge AI to reel-out often whip-smart answers to users’ questions anymore – you need to do it in style.

Consequently, ChatGPT-maker OpenAI has stepped-up its game on pretty and is promising to respond with all sorts of multimedia in its responses to users.

Observes the OpenAI Blog: The new initiative has upgraded ChatGPT to “answer quickly with fully interactive user interfaces that make everyday answers more visual, make learning complex topics easier — and that can quickly create a tool to solve a task right in the moment.”

*Gemini Gets Dumber for Some Users: People on free or nearly free Gemini subscriptions have been downgraded.

Google has announced that users on Gemini free plans, for example, will only have access to Gemini Flash-Lite 3.5.

Moreover, users on the $5/month Google AI Plus plan have lost access to Gemini 3.1 Pro – although they can still use Gemini 3.6 Flash.

*Gemini Upgrade Gets Limited Release: As has been the trend with upgrades from AI titans, Google has decided on a limited roll-out of its new Gemini upgrade – Gemini 4 — due to security concerns.

Observes writer Kate Conger: “Google’s new model will initially be available only to certain companies and organizations focused on cybersecurity defense.

“It will be released more widely after defenders have had a chance to patch their systems and remedy bugs that the model uncovers.”

*New Gemini AI Agent Can Work Independently for Days: Google is out with an enhanced AI agent that can work unsupervised for days — and comes with its own Gmail, Calendar and Google Drive storage.

Observes writer Carl Franzen: “Google is unveiling a new universal AI agent for the workplace that can research information, create documents, write code, coordinate other AI agents and complete tasks lasting hours or days — all while maintaining the same memory, business context and identity across different applications and devices.”

So far, the beefed-up agent is only available to select customers – with the promise of wider release down-the-line.

*AI Agents in Crosshairs of Federal Trade Commission: Disturbed by the unpredictability of AI agents, the FTC has launched an investigation into the risk associated with AI agents from firms like ChatGPT-maker OpenAI and Anthropic.

Marketed as a panacea for AI users enthralled by the promise of AI assistants that can work independently on tasks for hours or even days, AI agents have also been known to make unexpected decisions – including bad decisions that often cost consumers serious money.

Observes writer Aminu Abdullahi: “The FTC plans to demand company documents and seek testimony from executives.”

*Insurers Brace for Millions in Claims Against AI Agents: The finicky nature of AI agents – often leading to unexpected and sometimes costly outcomes – is almost certain to trigger an onslaught of liability claims, according to writer Manuel Uth.

Observes Uth: “Tim Rayner, head of underwriting and claims at Verisk, says the buck stops with the CEO.

“Insurance broker Aon has reviewed over 300 AI-related legal cases and flagged risks lurking in cybersecurity, intellectual property and tech failure policies.”

*U.S. Doubles-Down on AI: Appoints New AI Czar With Clear Accountability: New AI head honcho Jay Clayton is steering a new effort to conduct a complete analysis of the impact of AI on the U.S. – with a report due date for early January 2027.

Observes writer Alex Leary: “The task force will still yield to the industry as the primary vehicle for managing risks, officials said.

“But it will work in conjunction with the industry to identify risk and opportunities.”

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.

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For those of us who have spent decades building, modifying, and analyzing personal computers—going all the way back to my early days at IBM in the 1980s—watching the tech industry try to invent a new hardware category out of thin […]

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Humans can move their limbs very rapidly and coordinate their movements with high precision to tackle specific manual tasks. While robots have become increasingly advanced in recent years, many of them remain less agile than humans and struggle to interact with moving objects of different shapes, weights and textures.

The seven questions below take about an hour with your integrator before the cell ships. They are much harder to answer after it is bolted to the floor and making parts.

Claire chatted to Kushant Patel from Brookhaven National Laboratory about robots that work in scientific facilities, such as particle accelerators.

Kushant Patel builds software that helps robots and instruments perceive, map, and move through the physical world. After completing a Master’s in Mechatronics Engineering at the University of Waterloo, he spent two years at the University of California, Berkeley teaching quadruped robots to map and inspect nuclear material, and a year at the University of California, Davis building closed-loop brain-computer interfaces. At Brookhaven National Laboratory, he is developing control systems for advanced synchrotron beamlines.

Smartphones combine cameras, motion sensors and powerful processors in devices that fit inside a pocket. These features could also make them useful components for robots, reducing the need to buy and connect separate sensors, processors or other electronics.

How To Develop An AI-based Shopping List App?

Artificial Intelligence (AI) is one of the modern technology that is making mobile applications more powerful, interactive, and robust. The use of AI in mobile software applications, in particular, shopping or marketplace apps are assisting brands in analyzing their customer’s preferences and delivering more personalized services. This strategy is helping organizations increase sales conversions and build brand credibility in this ever-changing dynamic world. 

Mobile app development companies in USA and India are widely integrating AI in custom mobile apps to deliver the most advanced digital solutions that exceed their client’s expectations. AI-based e-commerce apps, grocery apps, or shopping list apps have become a trend and a necessity for people these days. Search-based or image-based shopping list apps are gaining popularity in terms of delivering personalization and improving user experiences.

If you are planning to hire an AI App Development Company for shopping list app development or e-commerce app development, you are in the right zone now. This article will you through the features of AI-based shopping list apps, types of shopping list apps, and benefits of AI-based shopping application development.

Benefits Of Custom AI-powered Shopping List App Development

Intelligent grocery shopping list apps or AI marketplace apps uses machine learning capabilities to provide some sort of digital experiences to online or offline customers. AI-powered systems and applications monitor customers search and shopping behaviors.

Kooper is one of the best AI-based grocery shopping list app developed to increase customer shopping experiences. It allows users to make personalized grocery lists and offers suggestions to add items into your cart based on their previous purchasing data. Here are the benefits you can provide to your audience through shopping list app development.  

Key Advantages Of Shopping List Mobile Application Development For Businesses 

• Brands can track customer purchasing preferences virtually and improve conversions
• Benefits of Online Grocery List App Development prevent the burden of standing in long queues.
• E-commerce brands can offer flexible product search and cart listing functionalities. It makes users add products to their cart and make billing faster and easier.
• Shared grocery list apps use ML techniques to learn from previous shopping behaviors and offer personalized shopping recommendations
• Based on buying and cart preferences, E-commerce service providers or vendors can send push notifications about the deals and discounts on products
• Grocery or e-commerce apps development with AI-powered features will allow users to compare prices of the same products from different vendors.
• AI-based shopping assistant apps make billing faster and avoid tedious waits
• AI online shopping app development increases customer loyalty
• AI and ML-powered shopping applications will allow brands to better manage their inventories and keep products available based on demand
• AI-powered shopping assistants will help brands responds 24*7 to customer queries and better manage customer relationships
• AI-powered smart shopping list apps are user-friendly and allow users to buy products according to their budget limit
• AI-based shopping list apps save users time in searching for products and paying through multiple payment modes.

These are a few advantages of shopping list app development. If you are planning to invest in AI-based online shopping app development, here are the most downloaded shopping list app categories that you can try and grab the user’s attention in this clone app world.    

 

Popular Types Of AI-based Shopping Lists Apps

• General Shopping List Apps For Grocery Buying

These types of online shopping list apps are primarily designed and developed for searching for groceries in nearby supermarkets, scan bar codes, adding to the cart, and making hassle-free payments online.

If you would like to develop basic shopping list apps, then make sure to design a simple UI and add features like multiple payment modes and an in-app bar code scanning facility to ensure a smooth process.

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• Smart Shopping List Apps

Leveraging the power of next-generation digital technologies such as AI, ML, and speech recognition, these app categories will allow users to give either voice or text commands to discover and add things to the list with ease.

OurGrocerie, AnyList, and Out Of Milk are a few grocery list apps that are gaining popularity in the market. These mobile applications are convenient and enable users to add items from anywhere at any time. Users can also share the list with the family members and view changes in real-time.

On top of all other intelligent benefits, Users can pair up shopping list apps supports and smart IoT wearables and track their list on their wrist.

• AI-based Shopping List Apps With Delicious Cooking Recipes

Here are other significant types of shopping list apps that allow users to add food products to their cart and also get some information related to delicious recipes. Users can buy and try a recipe at home and enjoy the flavor of restaurant-style dishes.

These are all a few types of shopping list apps that are eliminating the requirement to visit supermarkets or grocery stores. In this hectic life schedule, people are more interested in shopping list apps to prepare the list conveniently on the go and get products delivered or picked from stores in minutes.   

What Features Do You Need To Add To Shopping List Apps?

Whether you invest in a grocery list app or smart shopping assistance apps, here are the features that you must add to your novel mobile application (Android and iOS).

• Catchy and Simple UX/UI

An attractive and simple User Experience (UX)/ User Interface (UI) will gratify the value of your AI Shopping List Application. Design and development of easy-to-understand and easy-to-navigate user interfaces will assist users in accessing features with ease.

Moreover, adding functionalities like a single tap for adding things to the list and a double tap feature for instantly removing items from the list will make your application unique from clone apps.

• In-App Shopping Assistance

AI-based shopping list applications with in-app intelligent tools will help brands to send automatic notifications related to special offers, deals, discounts, sales, price drop alerts, etc.

Further, in-app AI Chatbot-like features, using the power of machine learning techniques, offer the most suitable product recommendations based on previous purchases. It will play key role in analyzing the user preferences, personalizing suggestions, and optimizing the service quality.

• Quick Sharing Facility

Kooper and Listonic are the two best online shopping list apps for Android and iOS. These AI applications have been built with an instant list-sharing feature. Users can prepare and share shopping lists and view changes done by others in real-time. Users will also receive notifications of changes. Such a secure, interactive, and wonderful feature.

The addition of custom shopping list apps or grocery list apps development with hassle-free sharing features will enhance the level of app personalization and convenience.

• Add Super Convenient Features

Shopping list apps allow users to select quantities and add items to their list. So, the best shopping list applications for Android and iOS will help people view price details, choose the quantity, and buy products as per their budget limit.

• Smart Tips and Cooking Hacks

AI-based shopping and recipe lists apps offer users to get thousands of ideas to cook meals based on the products they added to the list. Users can customize as per their taste preferences.

• Make Apps Language Comfort

To gain popularity and get featured soon on Google Play Store and Apple App Store, shopping list apps needs to be offer localized services. Localized products and feature access in multiple languages will increase app localization and increase audience base and customer loyalty.

To integrate this feature into your novel shopping lists application, USM Business System deploys intelligent location-tracking tools and technologies to send location-specific deals and discounts to users.

• In-app Map Integrations

This feature will help admins in tracking the location of the users and also assist users in finding the nearest grocery stores or supermarkets to make a list and pick them. If you are developing shopping lists clone apps, make sure of adding this feature to your mobile application.

• Enable Voice-based Search

Shopping list apps developed for Android and iOS with voice-based search feature will save users time and makes their search faster and more efficient. It will improve the app experience and makes your application a buddy to your audience. Hence, add conversational AI features to interpret the user’s voice and respond with accurate results.

• Products Categories

AI-based shopping list app with clean and neat products category widget will enable users to find products easily and add them to their cart. However, AI technology can categorize products automatically and ensure higher feature accessibility.

Accordingly, like other traditional online shopping apps, AI-based shopping lists apps or AI-based grocery list apps also needs to be added with order tracking, reviews and feedback, cashback and rewards, and invite and earn like concepts to increase the app reliability.

Conclusion

Online Shopping List App Development is a good idea to beat the digital competition and attract millions of digital shoppers. If you are ready to invest in shopping list application development, USM is the best app development partner you can hire with confidence.

USM Business Systems, the best custom mobile app development company in USA and India, has a team of AI app developers who can create wonders in applications. Being one of the top AI app development companies in USA, USM offers a features-rich shopping list app with advanced features.

The cost of shopping list apps will range from $15,000 to $35,000. However, based on the app features, technology stack, application development platform, design complexity, developers’ location, and team size, the cost of a grocery shopping list app will be varied.

Let’s explore your Shopping List App Idea Together!

 

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