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UCI Machine Learning Repository


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AiM Future Joins the Edge AI and Vision Alliance


AiM Future, a leader in embedded machine learning intellectual property (IP) for edge computing devices, announced it has joined the Edge AI and Vision Alliance. AiM Future is accelerating the transition from centralized cloud-native AI to the distributed intelligent edge. Its market-proven NeuroMosAIc Processor (NMP) family of machine learning hardware accelerators and software, NeuroMosAIc Studio, enables the efficient execution of deep learning models common to computer vision applications. "It is our company's pleasure to join the Edge AI and Vision Alliance," said ChangSoo Kim, founder, and CEO of AiM Future. "As a premier organization for technology innovators revolutionizing artificial intelligence across the edge computing spectrum, the partnership is a natural fit. It is clear AiM Future's vision of bringing the impossible to reality is shared by the Alliance and its ecosystem. The field of edge AI is rapidly advancing and partnerships are fundamental to addressing the many challenges and limitations of today's edge devices."

Preparing for quantum: next steps for enterprise


Investment in quantum technologies will grow from US$412mn in 2020 to US$8.6bn by 2027, according to research firm IDC. Organisations that get started now will have a significant competitive advantage over those that continue to wait until quantum computing is a proven technology. Nevertheless, the complexity of quantum hardware and software development are forcing organisations to invest significantly in elite quantum expertise just to explore quantum-possible use cases for their potential business value. Gordon Davey is Cloud Services (Microsoft) General Manager at SoftwareONE, a leading global provider of end-to-end software and cloud technology solutions. Davey said: "Quantum technologies within enterprises are expected to take off over the next five years, with forecasts estimating that the market will eventually be worth anywhere between $500mn to $29bn, according to IBM. The development of quantum computing is speeding up, and technology firms are partnering up with businesses to work on bringing out the first commercial applications. A great example of this is Goldman Sachs, who recently assembled a'full team dedicated to quantum computing', and JP Morgan, who is now looking to implement the use of quantum computers as well. Additionally, Willis Tower Watson has also partnered up with Microsoft to develop the potential of quantum computing."

Google sued for using the NHS data of 1.6 million Britons 'without their knowledge or consent'


Google is being sued over its use of confidential medical records belonging to 1.6 million individuals in the UK. The company's artificial intelligence arm, DeepMind, received the data in 2015 from the Royal Free NHS Trust in London for the purpose of testing a smartphone app called Streams. The claim is being brought by Andrew Prismall in a representative action in the High Court. It alleges that Google and DeepMind "obtained and used a substantial number of confidential medical records without patients' knowledge or consent". Why did Google get access to patient records?

Apply to more jobs in less time with LazyApply -- it's on sale for only $67


TL;DR: As of May 22, you can get a lifetime subscription to LazyApply Job Application worth $999 for just $67. It may feel counterproductive to start a job hunt by signing up for a service called LazyApply, but hear us out. The LazyApply job application software lets you apply to hundreds of jobs in a single click, so you're actually being more productive than you normally would -- thanks to a little thing called automation. Signing up for LazyApply can save you from having to constantly repeat the same tasks over and over again in your job search. Just add the extension to your Chrome browser, log in, add your résumé and other details, and begin the application process.

The Application of AI Technology in GPU Scheduling Algorithm Optimization


The Application of AI Technology in GPU Scheduling Algorithm Optimization | Zhancai Yan, Yaqiu Liu, Hongrun Shao | Artificial intelligence, Computer science, CUDA, GPU cluster, nVidia, Task scheduling

Research Papers based on Multi Agent Systems


This brief aims to sensitize the reader to EGT based issues, results and prospects, which are accruing in importance for the modeling of minds with machines and the engineering of prosocial behaviours in dynamical MAS, with impact on our understanding of the emergence and stability of collective behaviours.

Pharma 4.0TM -- Key Drivers, Game-Changers, Technologies


The Digital era has been a boon to the industry. But pharma manufacturers deal with increasingly complex challenges in this digital era. Pharma manufacturers need a holistic approach to increase quality, safety, transparency, agility, and productivity. Pharma 4.0TM, a term coined by ISPE (International Society for Pharmaceutical Engineering) is a concept adopted from Industry 4.0. The concept aims to bring in an interactive system, analytical data, advanced automation, and a simplified regulatory framework.

GrAI Matter Labs Launches Life-Ready AI 'GrAI VIP', A Full-Stack AI System-On-Chip Platform


GrAI Matter Labs unveils life-ready AI with GrAI VIP at GLOBAL INDUSTRIE. GrAI Matter Labs is a company in brain-inspired ultra-low latency computing that specializes in Life-Ready AI. Artificial Intelligence is the closest thing to natural intelligence. Artificial intelligence that feels alive. They make brain-inspired chips that act like people.

Need Help -- An AI / ML Enthusiast Professional with 18+ years of experience in SAP (ERP)…


Reaching out to you with a request for Career related advice / input. I am a professional with about 18 years of experience in advisory services and implementation of SAP solutions across industries and geographies, presently working with a consulting firm in the U.S. I am a Chartered Accountant from India by education. From 2018, I started focusing on ML/AI as my parallel interest / career in addition to SAP. For the last four years, I started putting efforts to learn fundamentals of the ML/AI domain. I read multiple blogs, books, completed courses as well as completed PoC for a few Embedded Machine Learning solutions of SAP.