Researchers from Purdue University recently demonstrated a method that allowed microchips to dynamically rewire themselves like the human brain to take in new data. The newly demonstrated technology allows artificial intelligence to learn over time.
It is a groundbreaking technology that can reshape the future of artificial intelligence and other high-end technologies.
The human brain constantly establishes new connections between neurons to facilitate learning. In contrast, the circuits on microchips do not change.
Purdue University researchers have created unique hardware that electrical pulses can reprogram on demand. It is a tiny rectangular device made with a hydrogen-sensitive material named perovskite nickelate.
Shriram Ramanathan, a professor in Purdue University’s School of Materials Engineering, said, “The brains of living beings can continuously learn throughout their lifespan. We have now created an artificial platform for machines to learn throughout their lifespan.”
Ramanathan is an expert in figuring out how to make materials that resemble the brain for better computing. According to him, the device’s adaptability will allow it to do all of the activities required to create a brain-inspired computer.
“If we want to build a computer or a machine that is inspired by the brain, then correspondingly, we want to have the ability to continuously program, reprogram and change the chip,” said Ramanathan.
The device can shuffle a concentration of hydrogen ions in nanoseconds by applying electrical pulses at varying voltages. This helps create states that the researchers found could be mapped out to corresponding activities in the brain.
The technology can act similar to a connection between neurons called synapses to store information in complicated neural circuits, with less hydrogen at that place. In this study, researchers also demonstrated that as new problems arise, a dynamic network may “pick and choose” which circuits are most suited to solving them.
Self-driving car manufacturing company Tesla revealed that it opted to remove a few microchips from some of its vehicles that are required for fully autonomous driving.
In Tesla’s Model 3 and Model Y vehicles, the manufacturer removed a few electrical control components from the steering wheels.
According to a CNBC report, Tesla was forced to do this due to the ongoing global chip shortage, and It was under pressure to meet its sales objective for the fourth quarter. Two Tesla employees and internal correspondence seen by CNBC revealed this information.
The removal of microchips was meant for cars in the Chinese market, but it is still unclear whether they were also made in cars for other markets. According to the report, a few vehicles might have also reached other countries like Germany, Australia, the United Kingdom, and others.
Tesla chose not to inform concerned customers about the chip’s removal as it would not pose a safety risk because it is part of a pair and serves as a backup for existing Tesla driver-assist systems. The affected vehicles will not be able to use Level 3 autonomous driving when they are updated ‘over-the-air.’
In order to make the affected vehicle capable of fully autonomous driving, the company has to retrofit the missing components in the cars. Tesla owners can currently only use Level 2 autonomous driving features, which do not require the dual-control electronic steering system for its functioning.
CEO of Tesla, Elon Musk, said, “My personal guess is that we’ll achieve full self-driving this year at a safety level significantly greater than a person. So the cars in the fleet essentially becoming self-driving via a software update, I think, might end up being the biggest increase in asset value of any asset class in history.”
The University of Florida (UF) partners with technology giant IBM to tackle multiple society’s biggest challenges.
As a part of this partnership, the University of Florida and IBM will jointly launch a comprehensive skills program aimed at extending UF’s vision of being a global leader in artificial intelligence, data science, fintech, and other related technologies.
This new development is a step towards the University’s goal of becoming the nation’s foremost AI University. According to the University, this partnership will be very beneficial in transforming the country’s workforce and boosting research capabilities.
The multi-year partnership with IBM includes plans to develop at least one new AI degree course and also online courses, tools, lecturers, and case studies from IBM’s Academic Initiative.
President of the University of Florida, Kent Fuchs, said, “By deepening our progress in artificial intelligence and other critical information technology, it will give our professors, scientists and students the right tools at the right time — benefiting everyone from teachers preparing schoolchildren for career success to doctors providing patients the very best health care to farmers growing more sustainable, healthier, productive crops.”
He further added that this new partnership with IBM puts them on the fast track to becoming a global leader in assisting the world in addressing the most significant challenges of the twenty-first century.
IBM and UF will collaborate to help instructors and students acquire varied and in-demand capabilities in artificial intelligence, cybersecurity, quantum cloud computing, and data science that align with industry demands and trends.
According to the plan, the partnership will extend to West Palm Beach in the coming future. IBM has pledged software and tools to UF in a memorandum of understanding, including hybrid cloud, to support the University’s AI and data science work.
Additionally, IBM will also assist in constructing a campus center devoted to financing and technology teaching, and research.
The United States Department of Defense selects artificial intelligence company Veritone for its new $249 million worth Blanket Purchase Agreement (BPA).
This fresh deal will help DoD to further expand the AI capabilities of the newly established Joint Artificial Intelligence Center (JAIC). The Veritone aiWARE, an AWS-certified platform, and essential applications for Test & Evaluation (T&E) capabilities will now be available to JAIC, allowing it to speed the government’s adoption of new AI technologies such as machine learning, deep learning, neural network, and many more.
Head of Government at Veritone, Jon Gacek, said, “To keep up with the ever-increasing velocity and influx of multi-intelligence (INT), the DoD must employ a platform that can accommodate bespoke AI models to extract actionable insights from each INT type, while also having the capability to test and evaluate all resulting model predictions at scale.”
He further added that they are honored to be one of the DoD’s chosen companies to help it achieve its mission of accelerating the delivery of AI-enabled technologies, scaling the department’s AI impact, and synchronizing DoD AI initiatives to extend Joint Force advantages. Earlier this month, DoD also selected data infrastructure provider Scale AI to boost the government’s artificial intelligence capabilities.
Veritone’s aiWARE platform allows customers to seamlessly enhance and automate deployment, integration, testing, assessment, and monitoring performance at scale while adhering to ethical standards and best practices.
Multiple industry-leading companies worldwide use Veritone’s AI-powered platforms to carry out their operations. “In addition to our recent successes within the DoD, Veritone aiWARE is gaining tremendous momentum within the civilian agencies too, including our FedRAMP authorization sponsored by the Department of Justice,” said President of Veritone, Ryan Steelberg.
Technology company NVIDIA announces that it has canceled its plans to acquire semiconductor company Arm. NVIDIA and SoftBank revealed this new development that provided much clarity on this matter.
Earlier, NVIDIA planned to acquire Arm from SoftBank Group through an acquisition deal worth $40 billion. However, reports surfaced earlier this month pointing towards this outcome as NVIDIA was unable to get approval for the deal.
Despite their best efforts, the parties agreed to terminate the agreement due to significant regulatory difficulties preventing the transaction from completion. As previous speculations materialize, SoftBank is preparing for Arm’s initial public offering.
Founder and CEO of NVIDIA, Jensen Huang, said, “Arm is at the center of the important dynamics in computing. Though we won’t be one company, we will partner closely with Arm. The significant investments that Masa has made have positioned Arm to expand the reach of the Arm CPU beyond client computing to supercomputing, cloud, AI, and robotics.”
He further added that Arm has a great future ahead of them, and NVIDIA will continue to support them as a proud licensee for many years to come. SoftBank, in a statement, mentioned that the deposit worth $1.25 billion paid by NVIDIA is non-refundable according to the signed agreement. Therefore the amount will be recognized as profit in the fourth quarter of the fiscal year ending March 31, 2022.
SoftBank believes Arm’s technology and intellectual property will remain at the forefront of mobile computing and artificial intelligence development.
“Arm is becoming a center of innovation not only in the mobile phone revolution, but also in cloud computing, automotive, the Internet of Things and the metaverse, and has entered its second growth phase,” said Representative Director, Corporate Officer, Chairman & Chief Executive Officer of SoftBank Group, Masayoshi Son.
He also mentioned that he wishes Jensen and his excellent team at NVIDIA all the best in their future endeavors.
The Indian Institute of Management (IIM) Bangalore announces the launch of its new certification program named Artificial Intelligence for Managers. Any graduate or experienced individual can readily apply for this course.
IIM Bangalore has meticulously designed the course curriculum to impart critical skills to learners, which would enable them to make better decisions using technologies like artificial intelligence and machine learning.
IIM Bangalore has priced the AI for Managers program at Rs 150,000 exclusive of tax. The program is of 15 months and contains ten new online, modular courses that are stacked together in a learning curve in the order they are completed.
Each course takes between 2 and 9 weeks, with enough time between modules for students to fully absorb the material. IIM Bangalore has included various modules related to data visualization, Data Preparation and Preprocessing, Foundations of Data Science, Predictive Analytics, Machine Learning with Business Applications, ML using Python, and several others in the curriculum of its newly launched AI for Managers certification program.
IIM Bangalore mentioned, “Use of AI and its components such as statistical learning, machine learning, and deep learning are expected to increase the stakeholder value and customer experience and be the main enabler for wealth creation.”
According to the institute, the new program provides numerous advantages to learners as it includes State-of-the-art pedagogical tools, education from India’s best management school, Peer2Peer learning through forums, project presentations, and more. After completing the course, learners will receive a certificate of completion from IIM Bangalore and edX. Learners will have access to an active community forum where they can resolve their queries. The registration process has already begun and will end on 31t March 2022. Interested candidates can apply for this AI for Managers course from the official website of IIM Bangalore.
Technology Giant Apple acquired an artificial intelligence startup named AI Music, reported Bloomberg. According to reports, the acquisition deal was completed in the past week.
However, no information was provided by the companies regarding the valuation of this acquisition deal. This new development will offer Apple access to AI Music’s cutting-edge technology that uses artificial intelligence to generate and compose music.
The company’s website suggests that its technology can produce soundtracks utilizing royalty-free music and artificial intelligence..AI Music’s highly capable technology creates dynamic soundtracks that change in response to the user’s actions.
For example, the soundtracks can be altered and adjusted depending upon the activity or mood the user is in, like gaming, workout, and many more. As stated on AI Music’s LinkedIn page, its motive is to “give consumers the power to choose the music they want, seamlessly edited to fit their needs or create dynamic solutions that adapt to fit their audiences.”
The acquisition will help Apply further strengthen its audio capabilities that can be used in multiple Apple devices in the future. Apple’s most recent purchase was also for Primephonic, a music startup. Apple now plans to integrate Primephonic’s classical music streaming service into an app related to Apple Music.
Apple has been relatively inactive for a few years in terms of acquisitions. According to a filing from October 2021, Apple only spent $33 million on contract payments for the fiscal year.
United Kingdom-based artificial intelligence startup AI Music was founded by Siavash Mahdavi in 2016. AI Music firmly believes that music should be accessible and contextually relevant for its creators and listeners. AI Music had previously worked with advertising agencies to create more engaging commercials that changed music depending on the viewer.
Researchers from the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS), Oregon State University, and their partners are now developing a unique machine learning-powered drone system that can be used to tackle the increasing concern of marine litter.
The newly developed drones would have smart sensors attached to them, helping them effectively dissect and map garbage along coastlines. Additionally, researchers are also coming up with innovative methods to collect the detected garbage.
Last year, the researchers used beaches near Corpus Christi, Texas, to test system devices and enhance detection methods.
“Our goal is to design and demonstrate a relatively low-cost, easily deployed, and accurate marine debris detection system that could be used by existing marine debris response programs,” said the researchers.
The developed drones will be equipped with polarimetric cameras to collect images. Researchers tested those polaroid cameras both on the ground and air using a helicopter with the assistance of the United States Coast Guard.
According to the team, the helicopter testing allowed them to replicate the height at which the drone system would be flown and simulate the functioning of the polaroid camera. The gathered pictures are then fed to a machine learning algorithm that identifies, classifies, and maps marine debris.
Over the past few decades, marine litter has become a significant issue of concern that threatens the aquatic life ecosystem, interferes with navigation safety, and poses a threat to human health. Every minute, 33,000 single-use plastic bottles are tossed into world oceans, adding to the millions of others already destroying marine life and the ecosystem.
This new ML-powered system will considerably help authorities to accurately and quickly clean the garbage disposed near coats. When the drone-based machine learning system is fully operational, the data collected will be utilized to generate maps that highlight where marine waste is accumulated along the coast.
Data science is said to be the hottest profession of the 21st century. With the buzz about its integral role in today’s business and research landscape, organizations are rushing to leverage it to achieve their enterprise goals. Companies are swiftly tapping on this emerging technology to harness the power of their data and offer more value to consumers, resulting in an increase in demand for data scientists.
Data science has been rapidly gaining traction in the industry and shows no signs of slowing down due to the development of advanced machine learning algorithms and a massive shift from descriptive to predictive analytics. This is where businesses look for new and experienced talents in the data industry who can come up with new ways to develop and experiment ahead of time.
In an exclusive interview with Dattaraj Rao, Chief Data Scientist of Persistent Systems, we tried to decipher the Data Science Culture at the company.
Founded in October 1990, Persistent Systems specializes in software product idea and design, agile product engineering, performance engineering, support assurance, quality assurance, and other technical services. Using an assortment of technologies like big data analytics, cloud, embedded systems, and security, the company has built solutions that center around promoting Responsible AI practices.
Building Trust with Responsible AI
As Responsible AI has become a necessary add-on while developing AI solutions today, companies like Persistent Systems are helping the tech industry get close to making this mainstream. Persistent Systems has a mature data science practice that helps it cater to its customers in Healthcare and BFSI domain through Responsible AI systems and solutions. Its Responsible AI strategy focuses on making AI/ML systems reproducible, transparent, accountable, private, and secure. For this, the company puts emphasis on standardization of the ML pipeline using MLOps patterns like data catalog, model registry, feature store, low-code ML, AutoML, data & concept drift monitoring, and Explainable AI (XAI).
Persistent Systems has benchmarked state-of-the-art Explainable AI libraries to understand model predictions and evaluate inherently interpretable glass-box models. Dattaraj explains ‘Model development may use standard frameworks like PyTorch, TensorFlow, Spark ML or we could leverage no-code/low-code ML tools like H2O.ai and PyCaret or we could use a Cloud stack like Sagemaker or Azure ML Studio.” He adds that while the actual tech stack may vary with the customer, the core patterns remain common and help in customer adoption.
Pre-requisites of A Successful Data Scientist
Dattaraj strongly supports the notion that a data scientist should be able to tell a good story with the data by clearly articulating how a problem is solved and verifying it with appropriate metrics. As someone with an engineering degree, he thinks a solid background in math and statistics is very important to succeed as a data scientist.
He acknowledges that the ability to use a library is impressive, but one needs to know the inner workings of the ML algorithms to be able to apply them correctly and tune models to solve a problem. In addition, a good data scientist should clearly understand the problem domain and the different types of data sources. Dattaraj says, “A significant amount of time is spent in understanding and cleansing the data and more effort you spend upfront will help you build better models.”
Data Science Hiring Practices at Persistent Systems
At Persistent Systems, Dattaraj reveals, there are multiple interview levels with programming exams to interviews on specific math and problem-solving skills. In addition to possessing the right mix of positive attitude and problem-solving skills, the hiring team also looks for candidates having a basic knowledge of a relevant domain. This is a must because, many times, data scientists have to decipher complex data sources and find useful features using the given resources. Therefore, having a knack for learning a new problem domain and being hands-on with data analysis tools can give the candidates an edge over the rest.
Along with the aforementioned, Dattaraj adds that Persistent Systems also values data science certifications. However, the final decisions about hiring a candidate will be primarily based on the skills, values, and problem-solving attitude they bring to the interview. Dattaraj also affirms that the industry experience of a candidate is always preferred since a major part of work for the data scientist is to understand the problem and data sources. Experience with solving a business problem is valuable, and industry experience will definitely be an advantage.
During the pandemic, Persistent Systems had no hassles in finding some amazing talent, and their hiring record is at an all-time high. According to Dattaraj, the company’s enterprise IT teams have adopted the same standards of excellence that it brought to its customers and faced no problem while transitioning to WFH culture. Persistent Systems adopts the best in class standards for network management and cybersecurity, making it possible for its engineers and data scientists to perform at maximum efficiency. Today, the company has talented minds from all over the world as an integral part of the Persistent family. Together, they help it offer unmatched results and performance that meet customer expectations.
Preparing for Dynamic Industry Demands
Speaking on future career scope, Dattaraj informs that AI/Ml is an extremely fast-evolving space. For better career prospects, candidates need to keep themselves updated on the latest research and upcoming trends. Consequently, Dattaraj encourages readers to catch up on research papers, blogs, conference videos published in their area of interest. The best thing about data science is there is so much material available for free on the internet. For example, there has been an influx of some unique ML models for text analytics in the last couple of years. Most of these are available for free and there are ready-to-run notebooks available at Google Colab, Kaggle, or Github that show example usage. New tools (like MLOps, AutoML, Feature stores)and patterns are continuously making the job of data scientists easier. In retrospect, candidates need to be at least aware of these concepts.
Words of Wisdom
Dattaraj asserts that today there are a lot of opportunities and avenues for someone aspiring to be a data scientist. He insists, “Keep learning and think of how you can make your and others’ jobs easier with the application of AI.”
Dattaraj claims to have witnessed many young data scientists who are very good programmers but don’t take the additional effort to understand ML algorithms and rely too much on the libraries and API calls. “I feel the time spent in understanding the basics behind models is definitely worth the effort and will make you better data scientists,” he concludes.
Digital services provider Tech Mahindra partners with conversational artificial intelligence company Yellow.ai to provide an enhanced experience to its customers.
The new partnership will allow Tech Mahindra to transform enterprise customer experiences with conversational AI. According to the plan, both the companies will work alongside to develop next-generation conversational artificial intelligence solutions.
The developed solution will come with multiple features and capabilities such as enterprise resource planning, supply chain management, human resource management system, customer relationship management, and several more, making the AI solution highly competent and versatile.
Head of Business Process Services at Tech Mahindra, Birendra Sen, said, “As organizations across the globe are shifting from transactional to conversational business models, we believe that conversational CX and EX solutions will revolutionize the way they do business. Our partnership with Yellow.ai is aimed at driving digital transformations in the CX and EX space.”
The AI-powered solution will help Tech Mahindra in multiple fields like optimizing resources, improving response time, and many more. The companies’ solutions will serve various industry verticals like telecommunications, media and entertainment, energy and utilities, automotive, healthcare, retail, and manufacturing.
Bengaluru-based customer experience automation startup Yellow.ai was founded by Anik Das, Jaya Kishore, Reddy Gollareddy, Raghu Ravinutala, and Rashid Khan in 2016. The company specializes in providing natural language processing-based customer experience automation platforms. Yellow.ai has almost 700 companies as customers and users in over 70 countries worldwide.
Co-founder and CEO of Yellow.ai, Raghu Ravinutala, said “With our joint offerings, we aim to redefine how enterprises connect with their customers, employees, and vendors. Combining a conversational layer built on our rich NLP engine with Tech Mahindra’s deep expertise in optimizing day-to-day business activities, our objective is to transform the future of work across a broad set of industries.”
He also mentioned that they are pioneering new ground with Tech Mahindra to provide enterprise customers with a competitive advantage through improved business process efficiencies.
