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Copyright: © Richard Jacobs
The Myntum Project is developing a blockchain-based digital "hot" vault to secure critical digital assets for consumers and businesses. Myntum's data flow will leverage the security principle of 2CIA—Confidentiality, Continuity, Integrity, and Availability of digital assets—and harness it to the immutable, traceable power of the blockchain, the Web 3.0.
Bharanidharan Rajakumar, CEO of TRANSFR VR (transfrvr.com), delivers a detailed discussion on the ways we learn and how virtual learning can help to improve skill level and job performance. Rajakumar has extensive experience and success in the development of user-friendly learning systems and was the founder of an automated tutoring platform for the education startup, LearnBop.
Rajakumar's company, TRANSFR VR, creates training simulations in virtual reality that enable employees and team members to develop the advanced skills needed to succeed on the job. The simulations are mentor-based VR training programs that provide truly personalized training to individuals that quicken learning and help with retention. From bartending to surgical skills, the spectrum is wide in terms of the innumerable career areas that could benefit from Rajakumar's learning simulation platform. With over 75 billion dollars spent on corporate training in the US, Rajakumar sees a particular need for training to be efficient and specialized in order for businesses to get the most bang for their buck. Manufacturing, hospitality, and nearly every industry has a need for quality training to enhance team member's skills, and TRANSFR VR is innovating to meet the needs, industry by industry. Rajakumar discusses the growing need for math skills on the job in multiple industries and how his platform allows companies to train employees using precisely the kind of math, in the exact work situation, that is tailored to the specific company. This kind of specialized training increases learning as employees use the actual tools and perform specific tasks in the virtual environment, just as they would on the job. Tailored training far surpasses general textbook math work.
Rajakumar's company's core technology can assess mastery of skills as it collects infinitely more data on users' interactions in the platform. As Rajakumar explains, on a traditional 2D screen, the data collected is more basic, such as what is being clicked on, how much time is being spent on a question, etc., but a virtual environment allows for an assessment of what the user is actually doing. With TRANSFR VR's virtual approach, applicants and employees feel less 'test anxiety' and are therefore more able to focus on their learning. As transparency is brought to both sides, stress levels are significantly reduced, which can lead to better results for employer and employee alike. Additionally, in regard to potential employees, they can experience the tasks of the job as they would in the real world, which expands their knowledge of what the job will be like. This advance knowledge helps to inform the candidate about the job such that they can more easily decide if it is a job they would like to pursue. And the obvious benefit to employers is that incoming employees will be more aware of the tasks required, how the job functions, etc., which tends to minimize turnover.
Rajakumar's platform is in demand internationally, but as his company is still expanding his plans are focused on engaging companies domestically for now, and especially in the areas that require mathematics and culinary skills. In any industry, employees and candidates require training to become proficient. Traditional methods of learning push us to learn at the same rate, but the truth is, people learn at their own rate, and Rajakumar's platform allows that to happen. People can make mistakes, try again, and never feel situational stress as they learn at their own rate, on their way to achieving a mastery of the skills needed.
As opposed to many other leaders in AI, the team at Qualcomm is a leader in edge computing that's conducted research for the past decade focused on optimizing, improving, and embracing machine learning and general AI algorithms on mobile processors without the need for a connection to the cloud. So, what's the advantage of on-device computing versus AI cloud players? Aside from improvements in energy consumption, there are actually three that are driving product development: performance, privacy, and reliability.
Since 2008, Qualcomm has been looking into neural networks and deep learning, but the past three years have brought an influx of compute capability and an abundance of algorithmic data, which lead to Qualcomm's release of one of the first mobile AI platforms and the Snapdragon 820 processor. Since then, Qualcomm has made numerous new developments and optimizations. Tune in to hear the details and to learn what's on the horizon.
To reach out for collaborations or find out about the latest developments, visit developer.qualcomm.com.
While it may not be immediately obvious, LinkedIn is one of the pioneers of machine learning. How so? Shivani Rao, applied researcher for the machine learning and relevance group at LinkedIn explains: "Every single product, every single feature, every single decision that's made involves data...and the AI algorithms have centered around personalized recommendations that are relevant to you based on your skills and activity on LinkedIn. Personalization is the key...and it requires data."
Among other topics, Rao discusses exactly how users receive a personalized experience via recommendations, the challenges encountered by LinkedIn and the ways they are being addressed, the tools that allow users to automatically send updates to recruiters, and the LinkedIn learning product which allows users to choose the skills they want to follow, ranging from management and leadership to C++ usability.
Tune in to hear the details, and visit Shivanirao.info for the latest news, outreach activities, and research.
Founded by three students studying artificial intelligence at Boston University around 2006, Neurala is a company that's using graphic processing units (GPUs) for artificial intelligence. Having identified the need for increased compute power, the team at Neurala found a way to essentially hack a GPU, making it more like a brain processor.
Since then, Neurala has developed technology that enables machine tool learning and is importing this technology to smart device applications, ranging from consumer apps on smartphones to enterprise solutions enabling complex inspections of structures.
"I believe our mission is to bring the AI industry to the next step, and the way we are doing that is by providing a different way to train this neural network...which resembles humans rather than the way they have been trained...which has been cumbersome...with systems that cannot improve anymore once being put on a device," says Massimiliano Versace, co-founder and CEO of Neurala.
In 2005, there were limited options; CPUs were being used but were already plateauing in terms of processor speed. Now, there is the availability of NPUs, or neural processing units, which are broadening the landscape of AI technology, its applications, and the impact it will have on our world.
Hit play to hear more about the differences between the brain and neural networks, Versace's outlook on the direction of the AI industry in the coming years, and the work being done by his team. Visit neurala.com to keep up on the latest developments.
James Sherer is an attorney and partner at Baker Law who joins the discussion today to discuss a variety of topics, including the ways in which AI is impacting hiring practices, healthcare, and data for sales. He also addresses the tougher questions, such as the ultimate goal of employing AI in these industries, and how to identify and mitigate algorithmic bias.
So, what are the main challenges and concerns that come along with the use of AI, and how far have we come in truly understanding the nature of its implementation in the industries so integral to our everyday lives? In which direction are we headed? Sherer gets into all of these details and more, so tune in for the whole discussion. To reach out with questions, email jsherer@bakerlaw.com or visit bakerlaw.com.
Blockpit aims to solve the complex topic of correct taxation in the fast growing market of cryptocurrencies. The goal is to bridge the gap between consumers and tax authorities on a global level by providing an easily accessable platform that will continuously evolve and adapt to the latest regulations. In addition to that, Blockpit will provide customized monitoring solutions for blockchain assets in different environments.
BlockSafe Technologies, Inc. is a US company incorporated in Wyoming with headquarters in Edison, NJ. The company has licensed patented technology from Strikeforce Technologies, Inc. and plans to enhance it with additional product offerings. Their team is comprised of people experienced in cyber security sales and operations. Our company is planning on an Initial Coin Offering (ICO) to raise funds for further product development and operations. BlockSafe solutions are built on multipatented and patent-pending technology and backed by 17 years of delivering cutting-edge cyber security.
Blockchain Defender™ — Security for permissioned blockchains such as those used by enterprises and industry consortia.
Exchange Defender™ — Security for crypto exchanges.
Crypto Defender™ — Security for crypto wallets on desktop, mobile, and cloud-based platforms, designed to prevent the harmful actions of malware.
Sebastien Roy is the CEO of Lean Systems. He is an experienced operation research developer with a wealth of embedded systems experience. Lean Systems is an optimization platform that enables fleet managers to increase overall productivity with a schedule and routes solver solution. Lean Systems' solver can schedule large fleets in the optimum way to produce efficiency and increase savings, and it can do this in only a few minutes at a cost that is scalable. And their platform can easily be integrated into any current information system.
Lean Systems' work involves the application of artificial intelligence (AI) to many problems that transportation companies face, such as pilot training, crew training, and more. Roy explains as fleets grow, so do the potential cracks in their training procedures. Resources and people get shuffled around and efficiency and quality can be compromised. With AI automation, Roy states tasks that once may have taken several days, such as scheduling for a fleet, can be done in a significantly shorter block of time. AI can consider multiple options, stops, destinations, etc. at once, which leads to faster, and better, scheduling, with greater compliance to crew preferences.
Roy details how one problem in the scheduling chain can create a domino effect of problems down the line, such as when a particular flight is cancelled or delayed and how that impacts crew and possible alternatives, etc. at the cancelled flight's destination points. Roy states that their platform can produce results that allow for an actual decrease in fleet size with an increase in efficiency and productivity of the fleet overall, as the AI can more easily address last minute problems with weather and maintenance.
The transportation efficiency expert addresses the traditional problems with fleet scheduling for the road and in the air. One issue that is perennially problematic is the scheduling of regulated maintenance, as maintenance schedules are mandated according to the number of actual flight hours of an aircraft. The problem loop exists as fleet managers need to book flights in order to know when an aircraft will need to go into maintenance but must consider maintenance schedules before booking flights.
Roy's company's platform allows fleet managers to use AI to run preemptive maintenance scheduling and thus decrease the hours needed for planning while increasing fleet efficiency. Overall, transportation companies can sell more flights while improving general crew satisfaction.
The LendingCoin (TLC) offers decentralized peer-to-peer funding via blockchain technology. Initially, funding will be limited to refinancing real estate within the United States but the long-term plan is to finance real estate purchases, refinance commercial and residential properties.
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