Traditionally, robots have excelled in specific tasks but struggled with versatility, requiring individual training for each unique job. However, this limitation might soon be a thing of the past.

Open X-Embodiment: The gateway to generalist robots

At the heart of this transformation lies the Open X-Embodiment dataset, a monumental effort pooling data from 22 distinct robot types.

With the contributions of over 20 research institutions, this dataset comprises over 500 skills, encompassing a staggering 150,000 tasks across more than a million episodes.

This treasure trove of diverse robotic demonstrations represents a significant leap towards training a universal robotic model capable of multifaceted tasks.

RT-1-X: A general-purpose robotics model

Accompanying this dataset is RT-1-X, a product of meticulous training on RT-1 – a real-world robotic control model – and RT-2, a vision-language-action model. This fusion resulted in RT-1-X, exhibiting exceptional skills transferability across various robot embodiments.

In rigorous testing across five research labs, RT-1-X outperformed its counterparts by an average of 50 percent.

The success of RT-1-X signifies a paradigm shift, demonstrating that training a single model with diverse, cross-embodiment data dramatically enhances its performance on various robots.

Emergent skills: Leaping into the future

The experimentation did not stop there. Researchers explored emergent skills, delving into uncharted territories of robotic capabilities.

RT-2-X, an advanced version of the vision-language-action model, exhibited remarkable spatial understanding and problem-solving abilities. By incorporating data from different robots, RT-2-X demonstrated an expanded repertoire of tasks, showcasing the potential of shared learning in the robotic realm.

A responsible approach

Crucially, this research emphasises a responsible approach to the advancement of robotics. 

By openly sharing data and models, the global community can collectively elevate the field—transcending individual limitations and fostering an environment of shared knowledge and progress.

The future of robotics lies in mutual learning, where robots teach each other, and researchers learn from one another. The momentous achievement unveiled this week paves the way for a future where robots seamlessly adapt to diverse tasks, heralding a new era of innovation and efficiency.

(Photo by Brett Jordan on Unsplash)

See also: Amazon invests $4B in Anthropic to boost AI capabilities

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Dojo was unveiled at Tesla’s annual AI Day last year but the project was still in its infancy. At AI Day 2022, Tesla unveiled the progress it has made with Dojo over the course of the year.

The supercomputer has transitioned from just a chip and training tiles into a full cabinet. Tesla claims that it can replace six GPU boxes with a single Dojo tile, which it says is cheaper than one GPU box.

Per tray, there are six Dojo tiles. Tesla claims that each tray is equivalent to “three to four full-loaded supercomputer racks”. Two trays can fit in a single Dojo cabinet with a host assembly.

Such a supercomputer naturally has a large power draw. Dojo requires so much power that it managed to trip the grid in Palo Alto.

“Earlier this year, we started load testing our power and cooling infrastructure. We were able to push it over 2 MW before we tripped our substation and got a call from the city,” said Bill Chang, Tesla’s Principal System Engineer for Dojo.

In order to function, Tesla had to build custom infrastructure for Dojo with its own high-powered cooling and power system.

An ‘ExaPOD’ (consisting of a few Dojo cabinets) has the following specs:

• 1.1 EFLOP
• 1.3TB SRAM
• 13TB DRAM

Seven ExaPODs are currently planned to be housed in Palo Alto.

Dojo is purpose-built for AI and will greatly improve Tesla’s ability to train neural nets using video data from its vehicles. These neural nets will be critical for Tesla’s self-driving efforts and its humanoid robot ‘Optimus’, which also made an appearance during this year’s event.

Optimus

Optimus was also first unveiled last year and was even more in its infancy than Dojo. In fact, all it was at the time was a person in a spandex suit and some PowerPoint slides.

While it’s clear that Optimus still has a long way to go before it can do the shopping and carry out dangerous manual labour tasks, as Tesla envisions, we at least saw a working prototype of the robot at AI Day 2022.

“I do want to set some expectations with respect to our Optimus robot,” said Tesla CEO Elon Musk. “As you know, last year it was just a person in a robot suit. But, we’ve come a long way, and compared to that it’s going to be very impressive.”

Optimus can now walk around and, if attached to apparatus from the ceiling, do some basic tasks like watering plants:

The prototype of Optimus was reportedly developed in the past six months and Tesla is hoping to get a working design within the “next few months… or years”. The price tag is “probably less than $20,000”.

All the details of Optimus are still vague at the moment, but at least there’s more certainty around the Dojo supercomputer.

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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The robot, which uses AI to play three chess games at once, grabbed and pinched the child’s finger. Unfortunately, despite several people rushing to help, the robot broke the kid’s finger:

According to Moscow Chess Federation VP Sergey Smagin, the robot has been used for 15 years and this is the first time such an incident has occurred.

Reports suggest the robot expects its human rival to leave a set amount of time after it makes its play. The child played too quickly and the robot didn’t know how to handle the situation.

“There are certain safety rules and the child, apparently, violated them. When he made his move, he did not realise he first had to wait,” Smagin said. “This is an extremely rare case, the first I can recall.”

It doesn’t paint Russia’s robotics scene in the best light and it’s quite surprising the story even made it out of the country’s notorious censorship.

Fortunately, the child’s finger has been put in a cast and he is expected to make a quick and complete recovery. There doesn’t appear to be any lasting mental trauma either as he played again the next day.

A study in 2015 found that one person is killed each year by an industrial robot in the US alone. As robots become ever more prevalent in our work and personal lives; that number is likely to increase.

Most injuries and fatalities with robots are from human error, so it’s always worth being cautious.

(Photo by GR Stocks on Unsplash)

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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Musk has been one of the most prominent figures to warn that AI is a “danger to the public” and potentially the “biggest risk we face as a civilisation”. In 2017, he even said there was just a “five to 10 percent chance of success [of making AI safe]”.

Speaking about London-based DeepMind in a New York Times interview last year, Musk said: “Just the nature of the AI that they’re building is one that crushes all humans at all games. I mean, it’s basically the plotline in ‘War Games’”.

Unveiling a 5ft 8in AI-powered humanoid robot may seem to contradict Musk’s concerns. However, rather than leave development to parties who he believes would be less responsible, Musk believes Tesla can lead in building ethical AI and robotics.

Musk has form in this area after co-founding OpenAI. The company’s mission statement is: “To build safe Artificial General Intelligence (AGI), and ensure AGI’s benefits are as widely and evenly distributed as possible.”

Of course, it all feels a little like building nuclear weapons to deter them—it’s an argument that’s sure to have some rather passionate views on either side.

During the unveiling of Tesla Bot, Musk was sure to point out that you could easily outrun and overpower it.

Tesla Bot is designed to “navigate through a world built for humans” and carry out tasks that are dangerous, repetitive, or boring. One example task is for the robot to be told to go to the store and get specific groceries.

Of course, all we’ve seen of Tesla Bot at this point is a series of PowerPoint slides (if you forget about the weird dance by a performer dressed as a Tesla Bot … which we’re all trying our hardest to.)

The unveiling of the robot followed a 90-minute presentation about some of the AI upgrades coming to Tesla’s electric vehicles. Tesla Bot is essentially a robot version of the company’s vehicles.

“Our cars are basically semi-sentient robots on wheels,” Musk said. “It makes sense to put that into humanoid form.”

AI Day was used to hype Tesla’s advancements in a bid to recruit new talent to the company. 

On its recruitment page, Tesla wrote: “Develop the next generation of automation, including a general purpose, bi-pedal, humanoid robot capable of performing tasks that are unsafe, repetitive or boring.

“We’re seeking mechanical, electrical, controls and software engineers to help us leverage our AI expertise beyond our vehicle fleet.”

A prototype of Tesla Bot is expected next year, although Musk has a history of delays and showing products well before they’re ready across his many ventures. Musk says that it’s important the new machine is not “super expensive”.

Find out more about Digital Transformation Week North America, taking place on 9-10 November 2021, a virtual event and conference exploring advanced DTX strategies for a ‘digital everything’ world.

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The pair announced their partnership in celebration of World Oceans Day and is part of Razer’s 10-year #GoGreenWithRazer campaign that will see the company make green investments to support environment- and sustainability-focused startups.

Patricia Liu, Chief of Staff at Razer, said:

“We are extremely happy to have the opportunity to work with a startup focused on saving the environment.

ClearBot’s unique AI and advanced machine learning technology will enable and empower governments and organisations around the world to broaden their sustainability efforts.

We urge other innovative startups to reach out to Razer for collaboration opportunities as we strive to make the world a safer place for future generations.”

Around eight million metric tons of plastic is dumped into the oceans each year. For perspective, that’s about 17.6 billion pounds worth—or the equivalent of 57,000 blue whales.

As these plastics break into smaller pieces due to wave action and sun exposure, these microplastics also end up in our food chain in addition to releasing chemicals that further contaminate the sea.

Hypoxic ‘dead’ zones – areas of such low oxygen concentration that animal life suffocates and dies – are on the increase. In 2004, scientists found 146 hypoxic zones. By 2008, that number had swelled to 405. In 2017, scientists found a dead zone in the Gulf of Mexico equivalent to the size of New Jersey.

The team behind ClearBot design robots that leverage AI-powered computer vision to identify marine waste and retrieve it to be responsibly disposed of.

Sidhant Gupta, Chief Executive Officer at ClearBot, commented:

“The Razer team’s action-oriented approach to solving marine waste issues was extremely eye-opening. We are grateful to the team who volunteered their time for this project.

With the new model, we’re confident in extending our reach globally to protect marine waters, starting with partners which include marine harbour operators in Asia and NGOs who have already expressed interest.

Together with Razer, we look forward to effecting positive change for the world.”

ClearBot is calling on the community to upload photos of marine plastic waste commonly found in open waters to their website that will be used to help improve the robot’s waste-detection AI algorithm.

You can find out more about World Oceans Day from the United Nations’ website here.

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Pepper will be attempting to explain topics such as AI and robotics to The Commons Education Select Committee.

“If we’ve got the march of the robots, we perhaps need the march of the robots to our select committee to give evidence,” Committee chair Robert Halfon told Tes.

“The fourth industrial revolution is possibly the most important challenge facing our nation over the next 10, 20, to 30 years.”

AI and robotics will drastically change our societies, and not always for the better. There will be serious challenges ahead.

It’s rare to hear of AI being discussed without the potential impact on jobs. Low-skilled workers, in particular, are most threatened by automation replacement.

The Select Committee will be looking to understand what impacts the fourth industrial revolution will have and how the negatives can be reduced. They’re hoping Pepper can help, though it all feels somewhat a gimmick.

“This is not about someone bringing an electronic toy robot and doing a demonstration,” said Mr Halfon. “It’s about showing the potential of robotics and artificial intelligence and the impact it has on skills.”

Pepper is equipped with four microphones, two HD cameras, and a touchscreen on its chest for displaying information when needed.

We caught up with Pepper at MWC earlier this year:

Fortunately, Pepper is experienced with public speaking after featuring on stages around the world. The robot could perhaps even offer advice to some leading tech company CEOs on coming across more human.

 Interested in hearing industry leaders discuss subjects like this? Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London, and Amsterdam to learn more. Co-located with the IoT Tech Expo, Blockchain Expo, and Cyber Security & Cloud Expo so you can explore the future of enterprise technology in one place.

(Image Credit: Pepper at Opening Ceremony of the 28th Tokyo International Film Festival by Dick Thomas Johnson under CC BY 2.0)

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The so-called ‘Defense Advanced Research Projects Agency’ researches a range of innovative new technologies. Many of these advancements will have an impact beyond defence.

As such, DARPA’s funding initiative will be open to applications beyond the defence community. That means any AI project you’re involved with could be in the running to receive a nice cash boost.

DARPA is calling its campaign ‘AI Next’ and applications are now open. Previous similar initiatives from the agency have been wildly successful.

Back in 2004, DARPA held ‘Grand Challenges’ with a $2 million first-place prize. Challengers had to race autonomous vehicles.

In the first year’s race, there were no winners. Just a year later, five vehicles crossed the finishing line. The initiative was lauded for creating a huge leap for driverless cars.

Fast-forward three years and those vehicles were successfully navigating traffic as part of the ‘Urban Challenge’ by DARPA.

In fact, even Siri (yes, the one which may be on your iPhone right now) was first created in part from DARPA funding. We’re talking before it was acquired by Apple, back when it was developed by SRI in Menlo Park.

DARPA is looking to make a similar leap in artificial intelligence with its AI Next initiative. The agency is focusing on the ‘third wave’ of AI which adds “contextual reasoning” (otherwise known as common sense to most of us).

That means future AIs will be able to analyse scenarios they’ve not been specifically trained for, much like humans.

Beyond simply being able to recognise there’s a person stood on the beach with a bottle of water, for example, it could notice things such as sand on the knees and equipment lying around which suggests the individual is hydrating after a game of volleyball.

This category in DARPA’s initiative is aptly called ‘Machine Common Sense’. Others include ‘Learning with Less Labels’ which aims to reduce the cost of labelling data, and ‘Lifelong Learning Machines’ which focuses on machines’ ability to transfer what’s been learnt from one environment into another.

You can apply for the funding here if your project is suitable.

 Interested in hearing industry leaders discuss subjects like this and sharing their use-cases? Attend the AI & Big Data Expo events with upcoming shows in Silicon Valley, London, and Amsterdam. Co-located with the IoT Tech Expo, Blockchain Expo and Cyber Security & Cloud Expo so you can explore the future of enterprise technology in one place.

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Some of a nation’s most vital infrastructure hides beneath the water. The difficulty in accessing most of it, however, makes important damage checks infrequent.

Sending humans down requires significant training and can take several weeks to recover due to the often extreme depths. There are far more underwater structures than skilled divers to inspect them.

Robots have been designed to carry out some of these dangerous tasks. The problem is until now they’ve lacked the smarts to deal with the unpredictable and rapidly-changing nature of underwater conditions.

Researchers from Stevens Institute of Technology are working on algorithms which enable these underwater robots to check and protect infrastructure.

Their work is led by Brendan Englot, Professor of Mechanical Engineering at Stevens.

“There are so many difficult disturbances pushing the robot around, and there is often very poor visibility, making it hard to give a vehicle underwater the same situational awareness that a person would have just walking around on the ground or being up in the air,” says Englot.

Englot and his team are using reinforcement learning for training algorithms. Rather than use an exact mathematical model, the robot performs actions and observes whether it helps to attain its goal.

Through a case of trial-and-error, the algorithm is updated with the collected data to figure out the best ways to deal with changing underwater conditions. This will enable the robot to successfully manoeuvre and navigate even in previously unmapped areas.

A robot was recently sent on a mission to map a pier in Manhattan.

“We didn’t have a prior model of that pier,” says Englot. “We were able to just send our robot down and it was able to come back and successfully locate itself throughout the whole mission.”

The robots use sonar for data, widely regarded as the most reliable for undersea navigation. It works similar to a dolphin’s echolocation by measuring how long it takes for high-frequency chirps to bounce off nearby structures.

A pitfall with this approach is you’re only going to be able to receive imagery similar to a grayscale medical ultrasound. Englot and his team believe that once a structure has been mapped out, a second pass by the robot could use a camera for a high-resolution image of critical areas.

For now, it’s early days but Englot’s project is an example of how AI is enabling a new era for robotics that improves efficiency while reducing the risks to humans.

What are your thoughts on the use of AI-powered robots for underwater checks? Let us know in the comments.

 Interested in hearing industry leaders discuss subjects like this and sharing their use-cases? Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London and Amsterdam to learn more. Co-located with the  IoT Tech Expo, Blockchain Expo and Cyber Security & Cloud Expo so you can explore the future of enterprise technology in one place.

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