Towards AI is a community that discusses artificial intelligence, data science, data visualization, deep learning, machine learning, NLP, computer vision, related news, robotics, self-driving cars, programming, technology, and more! From researchers to students, industry experts, and machine learning (ML) enthusiasts -- keeping up with the best and the latest machine learning research is a matter of finding reliable sources of scientific work. While blogs usually update in a more informal and conversational style, we have found that the sources in this list are accurate, resourceful, and reliable sources of machine learning research. Please know that the blogs listed below are by no means ranked or in a particular order. They are all incredible sources of machine learning research.
To quench algorithms' seemingly limitless thirst for processing power, IBM researchers have unveiled a new approach that could mean big changes for deep-learning applications: processors that perform computations entirely with light, rather than electricity. The researchers have created a photonic tensor core that, based on the properties of light particles, is capable of processing data at unprecedented speeds, to deliver AI applications with ultra-low latency. Although the device has only been tested at a small scale, the report suggests that as the processor develops, it could achieve one thousand trillion multiply-accumulate (MAC) operations per second and per square-millimeter – more than twice as many, according to the scientists, as "state-of-the-art AI processors" that rely on electrical signals. IBM has been working on novel approaches to processing units for a number of years now. Part of the company's research has focused on developing in-memory computing technologies, in which memory and processing co-exist in some form.
Artificial Intelligence (AI) is not just a buzzword, but a crucial part of the technology landscape. AI is changing every industry and business function, which results in increased interest in its applications, subdomains and related fields. This makes AI companies the top leaders driving the technology swift. AI helps us to optimise and automate crucial business processes, gather essential data and transform the world, one step at a time. From Google and Amazon to Apple and Microsoft, every major tech company is dedicating resources to breakthroughs in artificial intelligence. As big enterprises are busy acquiring or merging with other emerging inventions, small AI companies are also working hard to develop their own intelligent technology and services. By leveraging artificial intelligence, organizations get an innovative edge in the digital age. AI consults are also working to provide companies with expertise that can help them grow. In this digital era, AI is also a significant place for investment. AI companies are constantly developing the latest products to provide the simplest solutions. Henceforth, Analytics Insight brings you the list of top 100 AI companies that are leading the technology drive towards a better tomorrow. AEye develops advanced vision hardware, software, and algorithms that act as the eyes and visual cortex of autonomous vehicles. AEye is an artificial perception pioneer and creator of iDAR, a new form of intelligent data collection that acts as the eyes and visual cortex of autonomous vehicles. Since its demonstration of its solid state LiDAR scanner in 2013, AEye has pioneered breakthroughs in intelligent sensing. Their mission was to acquire the most information with the fewest ones and zeros. This would allow AEye to drive the automotive industry into the next realm of autonomy. Algorithmia invented the AI Layer.
This research summary is just one of many that are distributed weekly on the AI scholar newsletter. To start receiving the weekly newsletter, sign up here. Artificial intelligence (AI) has grown tremendously in just a few years ushering us into the AI era. We now have self-driving cars, contemporary chatbots, high-end robots, recommender systems, advanced diagnostics systems, and more. Almost every research field is now using AI.
"I tried to stay with some of the things that I know will be happening because we have some control of them," said Mr. Vogels. On Wednesday, he shared eight predictions based on customer-behavior patterns and technology investments by the company. The cloud will be everywhere. Next year will see more devices and more organizations powered by the cloud. Mr. Vogel, whose expertise in scalable systems led him to Amazon.com in 2004, predicts that the cloud in 2021 will continue to move beyond the traditional notion of a centralized system, with troves of data moving back and forth between customers and massive data centers in real time.
As we make tremendous advances in machine learning and artificial intelligence technosciences, there is a renewed understanding in the AI community that we must ensure that humans being are at the center of our deliberations so that we don't end in technology-induced dystopias. As strongly argued by Green in his book Smart Enough City, the incorporation of technology in city environs does not automatically translate into prosperity, wellbeing, urban livability, or social justice. There is a great need to deliberate on the future of the cities worth living and designing. There are philosophical and ethical questions involved along with various challenges that relate to the security, safety, and interpretability of AI algorithms that will form the technological bedrock of future cities. Several research institutes on human centered AI have been established at top international universities. Globally there are calls for technology to be made more humane and human-compatible. For example, Stuart Russell has a book called Human Compatible AI. The Center for Humane Technology advocates for regulators and technology companies to avoid business models and product features that contribute to social problems such as extremism, polarization, misinformation, and Internet addiction. In this paper, we analyze and explore key challenges including security, robustness, interpretability, and ethical challenges to a successful deployment of AI or ML in human-centric applications, with a particular emphasis on the convergence of these challenges. We provide a detailed review of existing literature on these key challenges and analyze how one of these challenges may lead to others or help in solving other challenges. The paper also advises on the current limitations, pitfalls, and future directions of research in these domains, and how it can fill the current gaps and lead to better solutions.
The increasing levels of software- and data-intensive driving automation call for an evolution of automotive software testing. As a recommended practice of the Verification and Validation (V&V) process of ISO/PAS 21448, a candidate standard for safety of the intended functionality for road vehicles, simulation-based testing has the potential to reduce both risks and costs. There is a growing body of research on devising test automation techniques using simulators for Advanced Driver-Assistance Systems (ADAS). However, how similar are the results if the same test scenarios are executed in different simulators? We conduct a replication study of applying a Search-Based Software Testing (SBST) solution to a real-world ADAS (PeVi, a pedestrian vision detection system) using two different commercial simulators, namely, TASS/Siemens PreScan and ESI Pro-SiVIC. Based on a minimalistic scene, we compare critical test scenarios generated using our SBST solution in these two simulators. We show that SBST can be used to effectively and efficiently generate critical test scenarios in both simulators, and the test results obtained from the two simulators can reveal several weaknesses of the ADAS under test. However, executing the same test scenarios in the two simulators leads to notable differences in the details of the test outputs, in particular, related to (1) safety violations revealed by tests, and (2) dynamics of cars and pedestrians. Based on our findings, we recommend future V&V plans to include multiple simulators to support robust simulation-based testing and to base test objectives on measures that are less dependant on the internals of the simulators.
Artificial Intelligence, an enigmatic term for technologies that make gadgets and software "smart," is expected to become a bigger part of our lives thanks to advances in computing power, data storage and high-speed networks such as 5G. San Diego is in a strong position to benefit from the expansion of artificial intelligence, according to a study "Measuring the Future: AI and San Diego's Economy" released last week from the San Diego Regional Economic Development Corp. While the study did not pinpoint a specific number of artificial intelligence jobs in the region, it did highlight industries with above-average employment in AI fields. They include telecommunications, information technology, software and transportation. Large companies with operations in San Diego such as Booz Allen Hamilton, Northrop Grumman and ResMed -- as well as smaller businesses such as Lytx, Lockton and Semantic AI -- are among the firms developing artificial intelligence technology in the region.
Artificial intelligence, an enigmatic term for technologies that make gadgets and software "smart," is expected to become a bigger part of our lives thanks to advances in computing power, data storage and high-speed networks such as 5G. San Diego is in a strong position to benefit from the expansion of artificial intelligence, according to a study "Measuring the Future: AI and San Diego's Economy" released last week from the San Diego Regional Economic Development Corp. While the study did not pinpoint a specific number of artificial intelligence jobs in the region, it did highlight industries with above-average employment in AI fields. They include telecommunications, information technology, software and transportation. Large companies with operations in San Diego such as Booz Allen Hamilton, Northrop Grumman and ResMed -- as well as smaller businesses such as Lytx, Lockton and Semantic AI -- are among the firms developing artificial intelligence technology in the region.