AI is expanding across the continent and new policies are taking shape. But poor digital infrastructure and regulatory bottlenecks could slow adoption.
Pilot season has officially begun for the world of humanoid robotics. Last year, Amazon began testing Agility’s Digit robots in select fulfillment centers, while this January, Figure announced a deal with BMW. Now Apptronik is getting in on the action, courtesy of a partnership with Mercedes-Benz.
According to the Austin-based robotics startup, “as part of the agreement Apptronik and Mercedes-Benz will collaborate on identifying applications for highly advanced robotics in Mercedes-Benz Manufacturing.” Specific figures have not been disclosed, as is customary for these sorts of deals. Generally, the actual number of systems included in a pilot are fairly small — understandably so, given the early nature of the technology.
Even so, these deals are regarded as a win-win for both parties. Apptronik can demonstrate clear interest from a leading automotive name, while Mercedes signals to customers and shareholders alike that it’s looking to the future. What comes next is what really matters. Should the pilot go well, causing the carmaker to put in a big order, that would be a massive feather in Apptronik’s cap — and the industry at large.
India will lower import taxes on certain electric vehicles for companies committing to invest at least $500 million and setting up a local manufacturing facility within three years, a policy shift that could potentially bolster Tesla’s plans to enter the South Asian market.
Companies must invest a minimum of $500 million in the country and will have three years to establish local manufacturing for EVs with at least 25% of components sourced domestically, according to a government press release on Friday. Firms meeting these requirements will be allowed to import 8,000 EVs a year at a reduced import duty of 15% on cars costing $35,000 and above. India currently levies a tax of 70% to 100% on imported cars depending on their value.
The policy change is likely going to pave the way for Tesla to enter India, as the Elon Musk-led company has been in talks with the government to lower import duties on its electric cars for years. The move also aligns with India’s goal to boost the adoption of EVs and reduce its dependence on oil imports, with the country setting a target of achieving 30% electric car sales by 2030.
Apple has added another AI startup to its acquisition list with Canada-based DarwinAI, which specializes in vision-based tech to observe components during manufacturing to improve efficiency, Bloomberg reported.
While Apple and DarwinAI haven’t announced this deal, several members of the startup’s team joined Apple’s machine learning teams in January, as per their LinkedIn profiles.
DarwinAI had raised over $15 million in funding across various rounds from investors, including BDC Capital’s Deep Tech Venture Fund, Honeywell Ventures, Obvious Ventures and Inovia Capital. BDC Capital confirms on its website that it has received an exit from DarwinAI, whereas Obvious Ventures has updated its portfolio to reflect that the startup has been acquired.
Just like Taylor Swift’s wildly successful Eras tour, Nvidia has taken center stage in their own widely successful AI Era tour. From Wall Street to Main Street, everyone is talking about Nvidia, and rightfully so. By powering the latest innovations in AI, Nvidia has achieved 126% revenue growth and 286% net income growth in the past fiscal year, an achievement most companies can only dream about, to become one of the most world’s most valuable companies. All of this is a result of being able to take existing core competencies like their GPU expertise and successfully applying it to an adjacent, yet still emerging use case like artificial intelligence (AI).
Much of Nvidia’s success can be attributed to one of its founders and the only CEO the company has ever had, Jensen Huang. Mr. Huang was recently recognized as one of the world’s most accomplished engineers with his election to the National Academy of Engineering (NAE), a nonprofit organization with more than 2,000 peer-elected members from industry, academia, and government that “provides engineering leadership in service to the nation.” This is a huge career achievement, one of the highest professional distinctions possible for an engineer.
Mr. Huang likes to say that “Nvidia innovates at the speed of light.” To his credit, Mr. Huang has continued to drive this kind of innovation at Nvidia since its inception. Nvidia was one of many companies developing graphics in the early days of PC gaming and one of the few to survive. Nvidia pioneered the Graphics Processing Unit (GPU) and was the first company to promote the concept of using GPUs for general computing purposes, which became known as GPGPU compute and led to the development of the Compute Unified Device Architecture (CUDA) software framework aimed at fully utilizing the massively parallel processing capabilities of Nvidia GPUs. With the advent of deep-learning techniques to train neural network models, Nvidia quickly adapted both its hardware and software solutions to enable an exponential growth in processing capabilities that led to the traditional and generative AI innovations that are sweeping the world today.
Learn about the incredible capabilities of Cerebras Systems’ new AI chip, the Wafer Scale Engine (WSE-3), with four trillion transistors.
A new research in battery technology now promises safer, longer-lasting energy storage. Thanks to a research team tackling a critical issue with solid-state batteries. The researchers have now developed a “bottom electrodeposition” method that changes the game for these next-generation power sources.
Today’s batteries say the ones in our smartphones or electric cars, mostly use liquid electrolytes for shuttling energy. However, these liquids are flammable, which obviously factors into safety concerns, even though they are minimal in today’s modern processes.
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Some major news outlets are about to release a feature known as “Content Credentials” to try and combat the spread of deepfakes. What are “Content Credentials”? Will it really stop deepfakes of Biden and Trump dancing together from spreading? Let’s have a look.
Continue reading “Credentials against Deepfakes: How will it work?” »
The calculation, which took around 75 days to complete, was carried out with 36 of the company’s proprietary solid-state drives (SSDs) — a storage medium fitted into many of the newest laptops — that stored altogether around 1 petabyte (1 million gigabytes) of data.
Processors are also needed to perform the number-crunching — with more powerful components reducing the time it takes to perform the necessary calculations. However, reliable and large-capacity storage is arguably more important because you need to store a massive amount of data in such a process.
The achievement “was no small feat,” Solidigm owner Brian Beeler said in the statement. “It involved meticulous planning, optimization, and execution.”
