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𝙈𝙚𝙚𝙩 𝙍𝙊𝙎𝘼: 𝙍𝙤𝙗𝙤𝙩 𝙜𝙪𝙞𝙙𝙚𝙨 𝙗𝙧𝙖𝙞𝙣 𝙨𝙪𝙧𝙜𝙚𝙧𝙮 𝙖𝙩 𝙃𝙤𝙪𝙨𝙩𝙤𝙣 𝙑𝘼

𝘛𝘩𝘦𝘳𝘦 𝘪𝘴 𝘢 𝘯𝘦𝘸 𝘴𝘶𝘳𝘨𝘪𝘤𝘢𝘭 𝘳𝘰𝘣𝘰𝘵 𝘪𝘯 𝘵𝘰𝘸𝘯. 𝘙𝘖𝘚𝘈, 𝘢 𝘳𝘰𝘣𝘰𝘵𝘪𝘻𝘦𝘥 𝘴𝘶𝘳𝘨𝘪𝘤𝘢𝘭 𝘢𝘴𝘴𝘪𝘴𝘵𝘢𝘯𝘵, 𝘩𝘢𝘴 𝘫𝘰𝘪𝘯𝘦𝘥 𝘵𝘩𝘦 𝘏𝘰𝘶𝘴𝘵𝘰𝘯 𝘝𝘈 𝘵𝘦𝘢𝘮 … See more.

Continue reading “Meet ROSA: Robot guides brain surgery at Houston VA” »

Many of the world’s top surgeons are learning first-hand what they can do with surgical robots — and it’s unlocking a new era in health care.

NVIDIA has launched a follow-up to the Jetson AGX Xavier, its $1,100 AI brain for robots that it released back in 2018. The new module, called the Jetson AGX Orin, has six times the processing power of Xavier even though it has the same form factor and can still fit in the palm of one’s hand. NVIDIA designed Orin to be an “energy-efficient AI supercomputer” meant for use in robotics, autonomous and medical devices, as well as edge AI applications that may seem impossible at the moment.

The chipmaker says Orin is capable of 200 trillion operations per second. It’s built on the NVIDIA Ampere architecture GPU, features Arm Cortex-A78AE CPUs and comes with next-gen deep learning and vision accelerators, giving it the ability to run multiple AI applications. Orin will give users access to the company’s software and tools, including the NVIDIA Isaac Sim scalable robotics simulation application, which enables photorealistic, physically-accurate virtual environments where developers can test and manage their AI-powered robots. For users in the healthcare industry, there’s NVIDIA Clara for AI-powered imaging and genomics. And for autonomous vehicle developers, there’s NVIDIA Drive.

The company has yet to reveal what the Orin will cost, but it intends to make the Jetson AGX Orin module and developer kit available in the first quarter of 2022. Those interested can register to be notified about its availability on NVIDIA’s website. The company will also talk about Orin at NVIDIA GTC, which will take place from November 8th through 11th.

In today’s multicultural society, language is the biggest barrier between the employer and the employee. And now as more opportunities for remote jobs are open, employees’ biggest fear is the language barrier or the different accents that might put them in a tough spot with the company they are applying for. Three Stanford students decided to encounter this problem after one of their own friends lost a customer support job due to his accent.

We decided to help the world understand and be understood, student Andres Perez Soderi, who is one of the founders of the new firm, told IEEE Spectrum. The friend group-turned-partners include a computer science major from China, an AI-focused management science and engineering major from Russia and a business-oriented MSE major from Venezuela.

After extensive research, the group found out that a lot of work had been done for voice conversion for deep fake technology but very little attention was given to accent translation. “We knew about accent-reduction therapy and being taught to emulate the way someone else speaks in order to connect with them. And we knew from our own experience that forcing a different accent on yourself is uncomfortable,” added Soderi. “We thought if we could allow software to translate the accent [instead], we could let people speak naturally.” Hence, in 2020 they started a company called Sanas which specializes in different accent translation.

Laser lidar startup Luminar, founded and led by the youngest self-made billionaire tracked by Forbes, will supply its sensors to Nvidia for a new autonomous vehicle technology platform that the chip and computing powerhouse is developing for automakers to install in consumer cars and trucks. The news pushed Luminar’s shares up more than 20%.

Nvidia aims to supply the DRIVE Hyperion system, powered by its Orin “systems on a chip” computing hardware, AI-enabled software and Luminar’s long-range Iris lidar, to automakers starting in 2,024 Luminar said at Santa Clara, California-based Nvidia’s annual GTC conference. The platform, which also integrates cameras and radar for additional sensing capability, includes everything needed for mass-production vehicles to operate autonomously in highway driving, Nvidia said earlier this year.

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Artificial intelligence (AI) has big promise to solve problems in almost every industry. AI-supported, AI-fueled, AI-based technologies are now present and capable of automating tasks in retail businesses and wealth management, to name a couple. These automations reduce error, manage increasingly vast datasets, and free up humans to do intelligent, strategic tasks. At the enterprise level, AI-architecture is transforming capacity and steadily shaping the way businesses of the future operate.

Connecting to Core Systems of Commerce Businesses Operationalizing machine learning or AI at scale is a key priority for the world of retail and commerce. Enterprise tech stacks leverage AI and predictions for high-frequency, ambiguous situations. Active learning and continuous improvement of AI are embedded in business applications and workflows. Making use of these requires contextual stitching of signals to create a single unified view of the truth, which empowers teams to make contextual decisions in the present. While the technological frameworks have existed for the better part of a decade, most businesses have been unable to overcome the barrier of applying technology in real world contexts, or at scale.

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Ohio-based startup Mantium has today announced closing $12.75 million in seed funding, as well as the launch of a cloud-based AI platform — which allows users to build with large language models.

The seed round, co-led by venture funds Drive Capital and Top Harvest, will be used to source for more talent, to add more features to Mantium’s AI platform and in driving awareness around what is achievable with large language models, especially across Africa, the firm’s CEO and co-founder Ryan Sevey told TechCrunch.

It is looking to expand its team of 33 which is currently spread across nine countries, including Ghana, Nigeria and Kenya. Having a globally distributed team, Sevey said, helps in the generation of unique insights and varying problem-solving approaches around AI.

Nvidia may be best known for graphics cards you can’t find in stores, but the company also makes some interesting software tools. An example of this is the noise removal feature known as RTX voice, which was upgraded to work with all GeForce cards earlier this year, and does an excellent job of cleaning up background noise.

Now Nvidia (Thanks, 80.lv) has been showing off a new tool in beta this year involving sound. Audio2Face is an impressive looking auto rigging process that runs within Nvidia’s open real-time simulation platform, Omniverse. It has the ability to take an audio file, and apply surprisingly well matching animations to the included Digital Mark 3D character model.

One of the things that many people hate most about getting vaccinations and taking certain types of medication is needles. Any medication that has to be delivered intramuscular typically requires a needle and a skilled medical professional to administer it. However, that may change in the future with a new autonomous robot created by a company called Cobionix, founded at the University of Waterloo.

The autonomous robot utilizes the company’s Cobi platform to perform injections without using needles. Cobi is described as a versatile robotic platform that can be deployed rapidly and complete tasks completely autonomously. The robot was fitted with a needle-free injection system. It demonstrated the ability to deliver intramuscular injections to patients without needing needles and without supervision by a healthcare professional.

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