Apptronik, an award-winning robotics company based in Austin, Texas, has planned to develop a general-propose robot called Apollo. The company focuses on costs and reliability from scratch, creating its own actuators to ensure they will be cost-effective and supply-chain friendly.
Jeff Cardenas, Apptronik co-founder and CEO, mentioned that the company is positioning Apollo as a high-performance, easy-to-use, versatile system. It imagines Apollo as an ‘iPhone of robots.’ He also stated that as a company, Approtronik had built more than 30 unique electric actuators, and now it is honored to start with its commercial humanoids.
The company’s importance on commercialization gives it a much different perspective on robotics development. According to Apptronik, to build a commercial robot, you must consider various aspects like minimizing part count, maintaining robustness, and keeping the overall costs manageable. The company’s starting point was to figure out what the minimum viable humanoid robot would look like.
Shaun Azmi, the leader of the Dexterous Robotics team at NASA’s Johnson Space Center, mentioned that the development of Apollo is the partnership to empower the development of technology to sustain through the Artemis program and looking forward to mars.
Google has unveiled a new AI system called “MusicLM” that can create high-fidelity music in any genre just with a text description, according to a research paper. However, the company is fearing the risks involved and says that it has no immediate plans to release it.
Google is not the first one to try generative AI for songs. There have been several other attempts, including Riffusion (an AI that composes music by visualizing it), Dance Diffusion, OpenAI’s Jukebox, and Google’s own AudioML.
However, due to limited training data and technical constraints, none of them have been able to generate songs that are particularly complex in composition or high fidelity. MusicLM is expected to be the first that can.
MusicLM was trained on a dataset of about 280000 hours of music to learn to generate coherent songs based on descriptions of significant complexity, such as Berlin ’90s techno with a low bass and strong kick or enchanting jazz songs with a memorable saxophone and a solo singer.
Its capabilities extend beyond creating short clips of songs. Google researchers showed that the system could build on existing melodies, whether played on an instrument, hummed, sung, or whistled.
A Bengaluru-based RV University has now banned the use of OpenAI’s ChatGPT. The university has banned the chatbot inside the campus to prohibit students from using it during the exams, assignments, and lab tests.
The university will check on students unexpectedly sometimes, and if the teachers get suspicious that the work submitted to them is not original, the student will be asked to do the work again by themselves.
Along with ChatGPT, the university has also banned the use of other AI-based tools such as GitHub Co-pilot and Black Box.
“We have issued an advisory to all departments in the university and banned a few AI tools like ChatGPT as students might use them in exams or to complete their assignments. The ban is already implemented,” a university spokesperson said.
New York City schools recently banned ChatGPT across devices and networks in all of New York’s public schools. According to a department spokesperson, the decision stems from the concerns about negative impacts on student learning and the safety and accuracy of the content.
Oreo, one of the most famous cookies company, has unveiled its metaverse called OREOverse, a virtual world where fans can compete and participate in cookie-themed activities.
The company introduced OREOverse with its new limited edition cookie called, ‘The Most Oreo Oreo.’ According to the company, the launch of OREOverse comes up with various prizes, including a $50,000 contest, virtual reality handsets, and gaming consoles.
Oreo has also collaborated with Martha Stewart, who is well-known for her bestselling recipes. Martha Stewart stated she is excited to make a metaverse debut in partnership with Oreo.
Julia Rosenbloom, Senior Brand Manager at Oreo, mentioned that the company is excited to enter into the metaverse. Oreo is thrilled to create new opportunities for its fans to connect and share the playful spirit.
On Monday, at 10.30 am ET, the company invites fans to tune in on Facebook or Instagram to watch Martha’s OREOverse excursion. Fans can dunk into OREOVerse in Meta’s Horizon World using their Meta Quest 2 or Meta Quest Pro headsets with mobile phones or desktop computers by visiting OREOverse.Oreo.com.
Square Yards, India’s largest real estate marketplace, announced the launch of its real estate metaverse. The real estate metaverse is a fully immersive and interactive environment, allowing users to explore the real estate on a digital twin of cities, visualize the neighborhoods in a 3D environment, and walk in as an avatar interacting with a collaborative marketplace.
Square Yards has secured many global patents on immersive, virtual, and collaborative experiences in real estate. The company is working with international real estate developers to bring their project twins onto its metaverse currently.
Square Yards arranged the metaverse launch event in Mumbai, which consisted of more than 150 attendees, like founders and CXOs of real estate developers and private equity investment professionals. The organization also hosted a panel discussion on ‘Metaverse and Digital Revolution of Real-Estate’ by Manisha Natarajan, the anchor and consulting editor at NDTV. The launch event featured demos of the Square Yards metaverse, showcasing its features and capabilities.
Founder and CEO of Square Yards, Tanuj Shori, stated that the company is very excited about the potential of the metaverse. He believes that Square Yards’ interactive digital twins of the cities will transform how consumers interact. The company has stepped into global markets like Dubai, Neom, and Canada in a short time with its patented digital twin tech.
Microsoft, GitHub, and OpenAI are pleading with the court to dismiss a proposed class action lawsuit that accuses these companies of scraping licensed code to create GitHub’s AI-powered Copilot tool, reported Reuters.
According to a pair of filings submitted to a San Francisco court, the Microsoft-owned GitHub and OpenAI say that the claims outlined in the lawsuit do not hold up. Launched in 2021, Copilot uses OpenAI’s technology to generate and suggest codes directly within the code editor of a programmer.
The tool, which has been trained using publicly available code from GitHub, caused concerns over whether it violates copyright laws right after its release. Things escalated when programmer and lawyer Matthew Butterick and the legal team at Joseph Saveri Law Firm filed a proposed class action lawsuit last November, claiming that the tool relies on “software piracy on an unprecedented scale.”
Butterick and his team later filed a second lawsuit on similar grounds on behalf of two anonymous software developers. This is the lawsuit that Microsoft, OpenAI, and GitHub want to be dismissed.
As noted in the filing, GitHub and Microsoft say the complaint fails on two intrinsic defects, lack of an otherwise viable claim and lack of injury. OpenAI similarly said the plaintiffs “allege a grab bag of claims that fail to plead violations of cognizable legal rights.”
According to the companies, the plaintiffs are relying on “hypothetical events” to back their claim and say they do not describe how they were personally harmed by the tool. The court hearing to dismiss the lawsuit will take place in May.
The promise of reducing traffic congestion and human-made accidents has caught our interest in autonomous vehicles for a decade. While we are still far from having fully autonomous vehicles hit the road, the idea of having self-driving cars steer us towards a new futuristic normal is undeniable. However, according to a new study from MIT, it might come at a massive cost.
In a startling revelation, MIT researchers found that the energy needed in the future to power just the computers on a worldwide fleet of autonomous vehicles could produce as much greenhouse gas emissions as all of the data centers in the world right now. The researchers discovered this while investigating the potential energy usage and associated carbon emissions in the likelihood that autonomous vehicles will receive wide adoption in the future.
It is well known that data centers that contain physical computing infrastructure that power online applications have a huge carbon footprint. The International Energy Agency estimates that data centers used about 200 terawatt-hours (TWh), or close to 1% of the world’s electricity demand, and contributed 0.3% of global CO2 emissions in 2018.
Noting insufficient research devoted to studying the possible carbon footprint of autonomous vehicles, MIT researchers developed a statistical model to investigate the issue. According to their findings, 1 billion autonomous vehicles, each powered by a computer using 840 watts, would be using enough energy to produce almost the same amount of global data center emissions from 2018. As a point of reference, there are presently about 1.5 billion automobiles on the planet’s roadways.
The researchers also discovered that in over 90% of the modeled scenarios, EV computers would need to consume less than 1.2 kilowatts (kW) of computing power just to stay within the existing range (below 2018 levels) of data center emissions, which is something we just cannot achieve with present hardware efficiencies. For instance, a different statistical model that examines a scenario in which 95% of all vehicles are autonomous by 2050 and computing workloads double every 3 years reveals that for emissions to remain at the current levels, hardware efficiencies in automobiles would need to double every 1.1 years. Meanwhile, the Moore’s Law rate, which has been widely recognized in the industry for decades, indicates that computer power doubles approximately every two or more years. To make things worse, this rate is anticipated to slow down rather than accelerate eventually.
Soumya Sudhakar, lead MIT researcher on the study, said that though the findings are only projections, they should urge those working on self-driving cars to understand that doing things “as usual” is insufficient and that computer efficiency should be a top priority. This is crucial to minimize the emissions from computers onboard autonomous vehicles. Soumya adds, “This has the potential to become an enormous problem. But if we get ahead of it, we could design more efficient autonomous vehicles that have a smaller carbon footprint from the start.”
The MIT team built a framework to study the operational emissions from the computers onboard a global fleet of autonomous electric vehicles. This model is dependent on several factors, including the total number of cars in the global fleet, the computing capacity of each computer on each vehicle, the hours driven by each vehicle, and the carbon intensity of the electricity that powers each computer. Because the MIT team is considering a future application that is not yet available, Soumya stated that each variable in the function equation involves a great deal of uncertainty. This was important because, according to some prior research, people might spend more time driving in autonomous vehicles since the hands-off steering wheel means multitasking! Autonomous vehicles could also encourage more younger and older drivers to get behind the wheel. At the same time, other research suggests that the amount of time spent driving can reduce as a result of algorithms discovering the fastest routes to destinations. Another problem is attempting to model for cutting-edge hardware and software technology that doesn’t yet exist.
As a result, researchers used a multitask deep neural network, a well-known method for autonomous cars, to mimic the workload of the algorithm. According to MIT, semi-autonomous vehicles currently use multitask-deep neural networks to navigate their surroundings by continuously receiving real-time data from several high-resolution cameras. Next, the research team explored several situations using the probabilistic model. They were surprised to learn how rapidly the workload of the algorithms increased.
According to one estimate, if a self-driving car employed ten deep neural networks to analyze video from 10 cameras for one hour of driving, it would produce 21.6 million inferences daily. Now consider how many inferences would be generated if one billion cars were used. 21.6 quadrillion conclusions! To put it into context, every Facebook data center in the world generates a few trillion inferences per day, reveals MIT. Imagine how energy-hungry autonomous vehicles are when put together!
Researchers suggested that to improve efficiency, engineers should create specialized hardware that would power navigation and perception tasks as well as run specific driving algorithms. However, Soumya noted that there is a problem with that, as cars frequently have lifespans of 10 to 20 years, and creating specific hardware now would create an additional challenge of making it “future-proof” so that it can support new algorithms.
The authors of the study suggested that researchers could also attempt to develop algorithms that are more effective and use less processing resources. However, that would mean compromising accuracy for effectiveness and possibly endangering vehicle safety.
After establishing this framework, the MIT teams intend to continue to investigate hardware efficiency and algorithm improvements in autonomous vehicles. Furthermore, they believe that characterizing embodied carbon from autonomous cars (i.e., the carbon emissions produced during the production of a car) and emissions from a vehicle’s sensors can improve their model.
The research, which has been published in IEEE Micro‘s January-February edition, was funded by the National Science Foundation and the MIT-Accenture Fellowship. The paper was co-authored by Soumya and her co-advisors, Sertac Karaman, an associate professor of aeronautics and astronautics and the director of the Laboratory for Information and Decision Systems (LIDS), and Vivienne Sze, an associate professor in the Department of Electrical Engineering and Computer Science (EECS) and a member of the Research Laboratory of Electronics (RLE).
Vivienne hopes that this research will motivate automakers to integrate emissions and carbon efficiency metrics into their designs.
Every business is always looking for ways to embrace technology and improve its operations. Technology helps companies work quicker, make fewer mistakes, and generally boosts the business as a whole. One of the most popular types of technology for businesses of all shapes and sizes is RPA (robotic process automation).
It has been catching on with businesses of all shapes and sizes and helps automate various tasks that would have had to be handled manually in the past. But what sorts of specific benefits does this technology provide? Well, that is precisely what this blog post will take a closer look at.
Take Your Customer Service to New Heights
Image Credit: Pixabay
One of the primary uses of RPA among businesses is to improve digital customer service. There are many adverse outcomes of bad customer service, so you want to ensure you are offering the best experience possible to customers who come to you with questions or concerns.
RPA takes customer service to the next level by automating much of the mundane, repetitive, and time-consuming work done by agents before, during, and after customer interactions. By taking these off their plate, agents have more time to focus on customers and help them through their issues.
RPA can help speed up response times, reduce disputes, and customers will be more satisfied with how smoothly their interactions with you have become. Customer demands are constantly changing, and they are always expecting more, and using RPA can ensure your service can meet those high demands.
Boost Overall Productivity and Efficiency
In many cases, the most significant benefit of RPA is that it will work wonders in helping your entire operation become more productive and efficient. RPA can dramatically improve productivity by letting employees take on the detailed and demanding tasks they are needed for and use robots to handle all of the mundane tasks.
Traditionally, workers spend a ton of time on work that can be automated, and RPA takes all of it off of their plates. This includes filing, copying, and pasting information, sending invoices, scheduling meetings, sorting emails, and many others. This gives them more time and energy to use on other work that may be more important.
When it comes to efficiency, robots, and automation, in general, can often perform tasks much quicker than would ever be possible manually. Humans can only work for a certain amount of time and need things like breaks and sleep, whereas robots can work around the clock.
Reduce Your Mistakes
Another major benefit of automation within your business is that it has the potential to reduce errors and mistakes. The high costs of business errors can be awful for your company, and you want to ensure you are accurate in all that you do.
No matter how well-trained someone is, they are still human and will thus make mistakes from time to time. However, robots are programmed to do the same thing each and every time, with a much lower chance of a problem or mistake taking place.
Of course, your RPA will need to be tested thoroughly to ensure it doesn’t make errors, but with the right testing and training, it can be a wonderful way to drastically reduce costly mistakes within your company.
In conclusion, these are just some of the many benefits that RPA can provide for your business.
The CEO of New York startup DoNotPay, Joshua Browder, recently announced that his company’s robot will represent a defendant to fight a traffic ticket in a courtroom on February 22.
“DoNotPay AI will whisper in somebody’s ear exactly what to say and what not to. We will release the results and share more with you after it happens,” he said.
However, we may never know how the “robot lawyer” will fare in court as after a few days, Browder announced that DoNotPay is putting on hold its court case after receiving jail threats from state bar prosecutors going through with his plan.
The CEO told NPR that several state bar associations had threatened their company, and one even said he could get imprisoned for six months. He told a media organization, “Even if it would not happen, the threat of criminal charges was enough to give it up.
Browder created DoNoPay as a free AI-powered chatbot that can help one draft letters and fill out forms for several legal matters, including the appeals for parking tickets.
The company’s “robot lawyer” uses several AI text generators, including DaVinci and ChatGPT, that have been trained to focus on law.
Uber Freight has laid off 150 employees, which is about 3% of the segment’s total head count. The unit marked $1.8 billion in revenue for 2022’s third quarter, up 336% year over year.
Uber Freight CEO Lior Ron said Monday that the layoffs affect the digital brokerage team of the division. These are the first layoffs since 2020, which were in the early weeks of the Covid lockdowns.
Uber had launched its freight unit in 2017 with the notion that trucking companies and laden goods can be matched using the same concept that underpinned the company’s ride-hailing technology.
“As you know, the logistics market is currently facing a number of headwinds which has impacted our customer base as well as the overall industry,” a spokesperson told the employees at Uber Freight.
“We accelerated hiring last year within certain areas of our Brokerage business, planning for a different economic reality, but the volumes did not materialize as expected,” he added.
Dara Khosrowshahi, Uber CEO, said last week at the World Economic Forum (WEF) in Davos that he is not planning company-wide layoffs.
