President Joe Biden on Tuesday will sign a bill to provide $52.7 billion in subsidies for U.S. semiconductor production and research and to boost efforts to make the United States more competitive with China's science and technology efforts. The White House is touting investments that chip companies are making even though it remains unclear when the U.S. Commerce Department will write rules for reviewing grant awards and how long it will take to underwrite projects. The chief executives of Micron, Intel, Lockheed Martin, HP and Advanced Micro Devices will attend the signing, set for 10 a.m. EDT, as will cabinet officials and auto industry and union leaders, including United Auto Workers President Ray Curry, the White House said. Also attending will be governors of Pennsylvania and Illinois, the mayors of Detroit, Cleveland and Salt Lake City, and lawmakers. The White House said the bill's passage was spurring new chip investments.

Google has sued Sonos, alleging that its new voice assistant violates seven patents related to its own Google Assistant technology, CNET has reported. It's the latest salvo in a long-running smart speaker battle between the companies, with each suing and countersuing the other following a period when they worked together. "[Sonos has] started an aggressive and misleading campaign against our products, at the expense of our shared customers," a Google spokesperson said in a statement. Sonos' Voice Control assistant arrived in June, letting users give commands with the phrase "Hey Sonos," much like Amazon's Alexa or Google Assistant. In the complaint, Google said it "worked for years with Sonos engineers on the implementation of voice recognition and voice-activated devices control in Sonos products... even providing its Google Assistant software to Sonos for many years."

One of the most exciting projects I have been lucky enough to work on at Intel was leading the engineering team tasked with designing, implementing and deploying the software platform that enabled large-scale training based on Habana Gaudi processors for MLPerf. I learned a lot on how to scale AI Training across a large hardware cluster, as well the challenges of building just building a data center. One thing that stood out was the immense amount of hardware, manual labor and power required to drive such a compute-intensive effort. Modern AI/ML solutions have shown that given a large amount of computing resources, we can create amazing solutions to complex problems. Applications leveraging solutions such as DALL·E and GPT-3 to generate images or create human-like research papers are truly mind-blowing.

AI Ethics Advisory Boards are essential but also require focus and attention, else they can fall ... [ ] apart and be untoward for all concerned. Should a business establish an AI Ethics advisory board? You might be surprised to know that this is not an easy yes-or-no answer. Before I get into the complexities underlying the pros and cons of putting in place an AI Ethics advisory board, let's make sure we are all on the same page as to what an AI Ethics advisory board consists of and why it has risen to headline-level prominence. As everyone knows, Artificial Intelligence (AI) and the practical use of AI for business activities have gone through the roof as a must-have for modern-day companies. You would be hard-pressed to argue otherwise. To some degree, the infusion of AI has made products and services better, plus at times led to lower costs associated with providing said products and services. A nifty list of efficiencies and effectiveness boosts can be potentially attributed to the sensible and appropriate application of AI.

Organizations have been planning to undergo a digital transformation for some time, and the pandemic has only accelerated things. How we conduct business has evolved, and we now have a more sympathetic perspective on client service and experience. The technology industry has advanced dramatically, and several innovations are becoming incredibly well-liked. Hyperautomation is one of them that has drawn widespread attention. The use of digital technologies by small, medium, and large businesses alike has been dramatically expedited by the epidemic.

Official - OCR - Convert image to text Multi Language Marks-Man submitted a new resource: [TheJavaSea] OCR - Convert image to text - Perform basic OCR (Optical Character Recognition) in English and 100 other languages. Our OCR application allows you to perform basic OCR (Optical Character Recognition) in English and 100 other languages. You must upgrade your account or reply to the thread to see the hidden content.

Speech AI can assist human agents in contact centers, power virtual assistants and digital avatars, generate live captioning in video conferencing, and much more. Under the hood, these voice-based technologies orchestrate a network of automatic speech recognition (ASR) and text-to-speech (TTS) pipelines to deliver intelligent, real-time responses. Building these real-time speech AI applications from scratch is no easy task. From setting up GPU-optimized development environments to deploying speech AI inferences using customized large transformer-based language models in under 300ms, speech AI pipelines require dedicated time, expertise, and investment. In this post, we walk through how you can simplify the speech AI development process by using NVIDIA Riva to run GPU-optimized applications.

The need for financial institutions to quickly operationalize their artificial intelligence capabilities has moved beyond important to imperative. More than supporting risk and fraud analysis, and increased productivity, a higher level of AI maturity at banks and credit unions will be a competitive differentiator, increasing business value across the organization. The banking industry must move out of the formative stages of AI deployment to help enhance human intelligence. This includes uncovering the drivers of key performance measures such as revenue and profit, and propelling innovation in products, services, processes and customer service. All financial institutions have the ability within reach to harness insights at scale – leveraging the right information, from the right people, at the right time.

Altana is an equal opportunity employer with a commitment to inclusion across race and ethnicity, gender, sexual orientation, age, religion, physical ability, veteran status, and national origin. We offer a comprehensive healthcare package and paid parental leave of 3 months for the primary caregiver and 1 month for the secondary caregiver.

The global population is growing at an alarming rate, and with it comes the challenge of finding new ways of producing enough food to feed everyone. The current state of the food production industry calls for a shift in strategy if we want to ensure that everyone has access to healthy and nutritious food in the future. Artificial intelligence (AI) is one of the key tools we need to achieve this goal. With AI, we can tackle complex problems, optimize processes, and produce results that would be much harder or even impossible to do manually. In this article, we will explore how AI will change how we feed the world, offer some valuable insights to farmers, and show where AI currently succeeds in food production and where it still has its limitations.