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Artificial Intelligence: Technology Trends


As artificial intelligence (AI) becomes more pervasive and embedded in life-changing decisions, the need for transparency has intensified. There have been plenty of high-profile cases in recent years where AI has contributed to bias and discrimination, with the use of facial recognition for policing just one example. There is a high probability of a shift from loose self-regulation to government involvement in AI over the next couple of years. In turn, Big Tech is increasingly using AI to solve the privacy and bias problems that the technology itself created. Listed below are the key technology trends impacting the AI theme, as identified by GlobalData.

Council Post: Business Leaders: Pay Attention To These Key Technology Trends


CEO of Align, Effortlessly turn your site into an advisor marketplace that generates revenue for experts and you. Every year, technology advancements continue to change business as we know it. The rate at which new devices, software and digital business methods are introduced continues to speed up into new frontiers. In addition, societal changes due to health, politics, geography and more have contributed to rethinking how business leadership has to perform today as opposed to just ten years ago. You don't have to be an IT expert to realize the organizational possibilities of these opportunities, either.

Machine Learning, AI, Carving Out Niches in Clinical Lab Management


While clinical labs' use of machine learning and artificial intelligence is perhaps most prominently associated with areas like pathology and microbiology testing, these tools are also seeing uptake for lab management applications like specimen routing and billing support. These kinds of logistical applications have proved particularly relevant during the COVID-19 pandemic, helping laboratories handle dramatic increases in testing demand, but investments in this technology has at some labs long pre-dated SARS-CoV-2.

Applying Machine Learning and AI Techniques to Data – The ODI


Learn to apply machine learning and AI techniques to data and discover how ethical frameworks can help you avoid teaching your machines bad habits. This course is essential for anyone needing a theoretical understanding of the opportunities and limitations of using machine learning on data. The course takes a practical approach to understand the key machine learning techniques, how they can be applied and what implications each has. Best of all, the course is designed to be non-technical. All practical exercises use drag and drop interfaces with virtual pens, post-its and paper.

What if Big Data Helped Judges Decide Exactly What Words Mean?


The precision and promise of a data-driven society has stumbled these past years, serving up some disturbing--even damning--results: facial recognition software that can't recognize Black faces, human resource software that rejects women's job applications, talking computers that spit racist vitriol. "Those who don't learn history are doomed to repeat it," George Santayana said. But most artificial intelligence applications and data-driven tools learn history aplenty--they just don't avoid its pitfalls. Instead, though touted as a step toward the future, these systems generally learn the past in order to replicate it in the present, repeating historical failures with ruthless, and mindless, efficiency. As Joy Buolamwini says, when it comes to algorithmic decision-making, "data is destiny."

Top 10 Upcoming AI and ML Conferences to Attend in 2021


From the business closure to economic turmoil, the year 2020 has disrupted every aspect of our lives. Many events, conferences and other meetings in technology have been cancelled or postponed. However, as many economic activities are coming to the new normal, many conferences are starting to take place both online and in person. Analytics Insight has listed here the top 10 upcoming AI and ML conferences that will help you decide which one to attend and which one suits you. With artificial intelligence and machine learning presenting new possibilities, AI and ML conferences are gaining much popularity.

Will Transformers Replace CNNs in Computer Vision?


This article is about most probably the next generation of neural networks for all computer vision applications: The transformer architecture. You've certainly already heard about this architecture in the field of natural language processing, or NLP, mainly with GPT3 that made a lot of noise in 2020. Transformers can be used as a general-purpose backbone for many different applications and not only NLP. In a couple of minutes, you will know how the transformer architecture can be applied to computer vision with a new paper called the Swin Transformer by Ze Lio et al. from Microsoft Research [1]. This article may be less flashy than usual as it doesn't really show the actual results of a precise application.

Why you may be counted by a 3D camera


The vaccine rollout is being met with lifted COVID-19 restrictions inside buildings and restaurants, but this change presents a new challenge to business owners -- managing increased occupancy, while still abiding by safety restrictions. Businesses that find themselves exceeding occupancy could face fines, citations, and license suspensions. One increasingly prominent solution employs 3D counting and tracking cameras that monitor occupancy, foot traffic, and flow inside brick-and-motor locations. Regular 2D cameras and traditional counting techniques are not accurate enough. However, depth-sensing 3D cameras can provide real-time updates that increase counting accuracy by an estimated 5% to 8%, according to a spokesperson for one 3D company I spoke with, Orbbec.

Harnessing Machine Learning to Accelerate Fast-Charging Battery Design


According to a new study in the journal Nature Materials, researchers from Stanford University have harnessed the power of machine learning technology to reverse long-held suppositions about the way lithium-ion batteries charge and discharge, providing engineers with a new list of criteria for making longer-lasting battery cells. This is the first time machine learning has been coupled with knowledge obtained from experiments and physics equations to uncover and describe how lithium-ion batteries degrade over their lifetime. Machine learning accelerates analyses by finding patterns in large amounts of data. In this instance, researchers taught the machine to study the physics of a battery failure mechanism to design superior and safer fast-charging battery packs. Fast charging can be stressful and harmful to lithium-ion batteries, and resolving this problem is vital to the fight against climate change.

This Is the Most Powerful Artificial Intelligence Tool in the World


In June 2020, the Californian company OpenAI announced GPT-2's upgrade to GPT-3, a language model based on artificial intelligence and deep learning with cognitive capabilities. It is a technology that has generated great expectations and that has been presented as the most important and useful advance in AI in recent years. OpenAI is a non-profit company founded by Elon Musk, co-founder and director of Tesla and SpaceX, which was born with the aim of researching and democratizing access to General Artificial Intelligence. Originally, it was a non-profit organization. However, in 2020, it became a company and partnered with Microsoft in order to achieve new advances, both in the field of language with GPT-3 models, and in the field of robotics and vision.