Introduction to Data Science

Data is a commodity which is wrapped with a process to make it valuable. Data science is a process to extract value from data in all its forms. Under this process, data from all its forms is compared and fine data is fetched for the further action. It basically refers to the collective processes, scientific theories, technologies, analysis, knowledge base and tools.

Spotlight

Mindteck

Mindteck, a global technology company established in 1991, provides Product Engineering solutions and Information Technology services to top-tier Fortune 100 companies, start-ups, leading universities and government entities. Its depth of knowledge and niche expertise in embedded systems and enterprise applications is complemented by dedicated Centers of Excellence in wireless design and storage testing.

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Software, Low-Code App Development, Application Development Platform

Are Telcos Ready for a Quantum Leap?

Article | July 3, 2023

Quantum technologies present both an opportunity for telcos to solve difficult problems and provide new services and a security threat that could require extensive IT investment. Are Telcos Ready for a Quantum Leap? When Andrew Lord, Senior Manager, Optical Networks and Quantum Research at BT, first started presenting quantum technologies at customer events six or seven years ago, his was the graveyard shift, he says, entertaining attendees at the end of the day with talk of 'crazy quantum stuff.' "But that is no longer the case," says Lord. "Over the last two years, I've noticed a shift where I now speak before lunch, and customers actively seek us out." Two developments may be causing the shift: Customers’ growing awareness of the threats and opportunities that quantum computing presents, plus a recent spike in investment in quantum technology. In 2022, investors plowed $2.35 billion into quantum technology startups, which include companies in quantum computing, communications and sensing, according to McKinsey. The public sector has also been digging deep into its pockets. Last year, the United States added $1.8 billion to its previous spending on quantum technology, and the EU committed an extra $1.2 billion, the consultancy noted, while China made total investments of $15.3 billion. According to Luke Ibbetson, Head of Group R&D at Vodafone, quantum computing's promise lies in solving a probabilistic equation within a few hours. This task would take a classical computer a million years to accomplish. This breakthrough would enable telcos to address optimization problems related to network planning, optimization, and base station placement. The flip side is that a powerful quantum computer could also break the public-key cryptography that protects today’s IT systems from hackers. As a spokesperson at Deutsche Telekom remarks: “Telcos will have to react to the threat of quantum computers to communication security because their core business model is at risk, which is offering secure digital communications.” The idea of quantum computing posing a security threat is not new. In 1994, Peter Shor, a mathematician working at AT&T Bell Labs, showed how a quantum computer could solve the logarithms used to encrypt data. “His work simultaneously ignited multiple new lines of research in quantum computing, information science, and cryptography,” according to an article by the Massachusetts Institute of Technology, where Shor is currently working. Beyond The Lab What has changed nearly thirty years on is that quantum computing is creeping out of the lab. Sizeable obstacles to large-scale quantum computing, however, remain. Quantum computers are highly sensitive to interference from noise, temperature, movement or electromagnetic fields and, therefore, very difficult and expensive to build and operate, especially at scale: IBM’s latest quantum processor, for example, operates at a very low temperature of approximately 0.02 degrees Kelvin. When Deutsche Telekom’s T-Labs tested telco use cases, it found quantum computing coped well with small problem statements. “However, when the problem size was scaled to real-world problem sizes, the quality of the QComp solution degraded,” according to the spokesperson. The company is now awaiting the next generation of quantum computing platforms to redo the analyses. All of this means, for now, quantum computers are not large and powerful enough to crack Shor’s algorithm. The question is, when will someone succeed? The Global Risk Institute tracks the quantum threat timeline. In its latest annual report, the organization asked 40 quantum experts whether they thought it likely that within the next ten years, a quantum computer would break an encryption scheme like RSA-2048 in under 24 hours. Over half the respondents judged the event to be more than 5% likely, and almost a quarter considered it to be more than 50% likely. Any breakthrough will come from a relatively small number of actors. Today, governments and academic institutions are home to around half of the 163 projects accounted for worldwide by Global Quantum Intelligence, a research and analysis company, according to its CEO, André M. König, with big technology companies and specialized startups accounting for the rest. Q2K Nonetheless, the impact of quantum computing could be widespread, even if relatively few of them are built. The challenge of preparing for a post-quantum future is often called Q2K in reference to the Y2K bug. In the late 1990s, many (but not all) governmental organizations and companies spent millions of dollars on Y2K systems integration to ensure that IT programs written from the 1960s through the 1980s would be able to recognize dates after December 31, 1999, all while being uncertain of the scale or the impact of the risk if they didn’t. ‘Q2K’ differs in that there is no specific deadline, and the dangers of a major security breach are much clearer cut. However, it is similar in demanding a lot of work on aging systems. “Cryptography is used everywhere,” points out Lory Thorpe, IBM’s Director of Global Solutions and Offerings, Telecommunications. She adds, “Because telco systems have been built over periods of decades, people don’t actually know where cryptography is being used. So, if you start to look at the impact of public key cryptography and digital signatures being compromised, you start to look at how those two things impact open source, how that impacts the core network, the radio network, [and] OSS/BSS, network management, how the network management speaks to the network functions and so on.” This complexity is why some analysts recommend that telcos take action now. “You’re going to find tens of thousands of vulnerabilities that are critical and vulnerable to a quantum attack. So, do you have to worry about it today? Absolutely - even if it’s in 2035,” says König. “Anyone who has ever done [IT implementation projects], and anyone who’s ever worked in cybersecurity [knows], tens of thousands of vulnerabilities that are critical [requires] years and years and years of just traditional integration work. So, even if you’re skeptical about quantum, if you haven’t started today, it is almost too late already.” Don’t Panic! For the past two to three years, Vodafone has been preparing to migrate some of its cryptographic systems to be quantum-safe, according to Ibbetson. He believes there is no need to panic about this. However, telcos must start planning now. König said, "The telecoms industry as a whole is not moving as quickly as some other sectors, notably the banking, pharmaceutical, and automotive industries. In these sectors, post-quantum security planning often involves CEOs at a very strategic level." For this reason, Vodafone joined forces with IBM in September 2022 to establish the GSMA Post-Quantum Telco Network Taskforce. “Even though many industries are preparing to be able to defend against future quantum threats, we didn’t see anything happening particularly in in the telco space, and we wanted to make sure that it was a focus,” says Ibbetson. “Obviously it will turn into an IT-style transformation, but it’s starting now with understanding what it is we need to mobilize that.” AT&T has also been working to pinpoint what needs to be addressed. Last year, the company said it aims to be quantum-ready by 2025, in the sense that it will have done its due diligence and identified a clear path forward. Minding Your PQCs Companies across multiple sectors are looking to post-quantum cryptography (PQC) to secure their systems, which will use new algorithms that are much harder to crack than RSA. König contends that PQC needs to become “a standard component of companies’ agile defense posture” and believes the development of PQC systems by software and hardware companies will help keep upgrade costs under control. “From a financial point of view, vendors do a fantastic job bringing this to market and making it very accessible,” says König. Lord, who has been researching quantum technologies at BT for over a decade, is also confident that there is “going to be much more available technology.” As a result, even smaller telcos will be able to invest in securing their systems. “It doesn't need a big boy with lots of money [for] research to do something around PQC. There’s a lot of work going on to ratify the best of those solutions,” says Lord. There are several reasons why eyes are on software based PQC. Firstly, it can be used to secure data that was encrypted in the past, quantum computing advances will make vulnerable in the future. In addition, the quantum-based alternative to PQC for securing network traffic called quantum key distribution (QKD), comes with a huge drawback for wireless operators. QKD is hardware-based and uses quantum mechanics to prevent interception across optical fiber and satellite (i.e., free space optical) networks, making it secure, albeit expensive. But for reasons of physics, it does not work on mobile networks. Setting Standards Given the importance of PQC, a lot of effort is going into standardizing robust algorithms. The political weight of the US and the size of its technology industry mean that the US government’s National Institute of Standards and Technology (NIST) is playing a key role in the technical evaluation of post-quantum standardization algorithms and creating standards. NIST expects to publish the first set of post-quantum cryptography standards in 2024. In the meantime, Dustin Moody, a NIST mathematician, recommends (in answers emailed to inform) that companies “become familiar and do some testing with the algorithms being standardized, and how they will fit in your products and applications. Ensure that you are using current best-practice cryptographic algorithms and security strengths in your existing applications. Have somebody designated to be leading the effort to transition. QKD There is no absolute guarantee, however, that a quantum computer in the future won’t find a way to crack PQC. Therefore, institutions such as government agencies and banks remain interested in using QKD fiber and satellite networks to ensure the highest levels of security for data transmission. The European Commission, for example, is working with the 27 EU Member States and the European Space Agency (ESA) to design, develop and deploy a QKD-based European Quantum Communication Infrastructure (EuroQCI). It will be made up of fiber networks linking strategic sites at national and cross-border levels and a space segment based on satellites. EuroQCI will reinforce the protection of Europe’s governmental institutions, their data centers, hospitals, energy grids, and more,” according to the EU. Telecom operators are involved in some of the national programs, including Orange, which is coordinating France’s part of the program called FranceQCI (Quantum Communication Infrastructure). Separately, this month, Toshiba and Orange announced they had successfully demonstrated the viability of deploying QKD on existing commercial networks. Outside the EU, BT has already built and is now operating a commercial metro quantum-encryption network in London. “The London network has three quantum nodes, which are the bearers carrying the quantum traffic for all of the access ingress,” explains Lord. For example, a customer in London's Canary Wharf could link via the network to the nearest quantum-enabled BT exchange. From there, it joins a metro network, which carries the keys from multiple customers “in an aggregated cost-effective way to the egress points,” according to Lord. “It is not trivial because you can mess things up and [get] the wrong keys,” explains Lord. “You really have to be more careful about authentication and key management. And then it's all about how you engineer your quantum resources to handle bigger aggregation.” It also gives BT the opportunity to explore how to integrate quantum systems downstream into its whole network. “What I'm telling the quantum world is that they need to get into the real world because a system that uses quantum is still going to be 90%, non-quantum and all of the usual networking rules and engineering practices apply. You still need to know how to handle fiber. You still need to know how to provision a piece of equipment and integrate it into a network.” SK Telecom is also heavily involved in quantum-related research, with developments including QKD systems for the control and interworking of quantum cryptography communication networks. Japan is another important center of QKD research. A QKD network has existed in Tokyo since 2010, and in 2020, financial services company Nomura Securities Co., Ltd. tested the transmission of data across the Tokyo QKD network. As the EU’s project makes clear, satellite is an important part of the mix. Lord expects satellite-based QKD networks to come on stream as of 2025 and 2026, enabling the purchase of wholesale quantum keys from a dedicated satellite quantum provider. Back in 2017, China already used the satellite to make the first very long-distance transmission of data secured by QKD between Beijing and Vienna, a distance of 7,000km. Securing The Edge There are additional efforts to secure communications with edge devices. BT’s Lord, for example, sees a role for digital fingerprints for IoT devices, phones, cars and smart meters in the form of a physical unclonable function (PUF) silicon chip, which, because of random imperfections in its manufacture, cannot be copied. In the UK, BT is trialing a combination of QKD and PUF to secure the end-to-end journey of a driverless car. The connection to the roadside depends on standard radio with PUF authentication, while transmission from the roadside unit onward, as well as the overall control of the autonomous vehicle network, incorporate QKD, explains Lord. SK Telecom has developed what it describes as a quantum-enhanced cryptographic chip with Korea Computer & Systems (KCS) and ID Quantique. Telefónica Spain has partnered on the development of a quantum-safe 5G SIM card and has integrated quantum technology into its cloud service hosted in its virtual data centers. Given China’s heavy investment in quantum technologies, it is no surprise to see its telecom operators involved in the field. China Telecom, for example, recently invested three billion yuan ($434m) in quantum technology deployment, according to Reuters. Quantum in The Cloud Some of America's biggest technology companies are investing in quantum computing. Today, it is even possible to access quantum computing facilities via the cloud, albeit at on small scale. IBM's cloud access to quantum computers is free for the most basic level, rising to $1.60 per second for the next level. And it is just the beginning. America's big tech companies are racing to build quantum computers at scale. One measure of scale is the size of a quantum processor, which is measured in qubits. While a traditional computer stores information as a 0 or 1, a qubit can represent both 0 and 1 simultaneously. This unique property enables a quantum computer to explore multiple potential solutions to a problem simultaneously; and the greater the stability of its qubits, the more efficient it becomes. IBM has a long history in quantum research and development. In 1998, it unveiled what was then a ground-breaking 2-qubit computer. By 2022, it had produced a 433-qubit processor, and in 2023, it aims to produce a 1,121-qubit processor. Separately, this month, it announced the construction of its first quantum data center in Europe, which it expects to begin offering commercial services as of next year. Google is also firmly in the race to build a large-scale quantum computer. In 2019, a paper in Nature featured Google’s Sycamore processor and the speed with which it undertakes computational tasks. More recent work includes an experimental demonstration of it’s possible to reduce errors by increasing the number of qubits. Microsoft reckons that "a quantum machine capable of solving many of the hardest problems facing humanity will ultimately require at least 1 million stable qubits that can perform 1 quintillion operations while making at most a single error." To this end, it is working on what it calls a new type of qubit, a topological qubit. Amazon announced in 2021 an AWS Center for Quantum Computing on the Caltech campus to build a fault-tolerant quantum computer.

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Software, Future Tech, Application Development Platform

Empowering Industry 4.0 with Artificial Intelligence

Article | July 24, 2023

The next step in industrial technology is about robotics, computers and equipment becoming connected to the Internet of Things (IoT) and enhanced by machine learning algorithms. Industry 4.0 has the potential to be a powerful driver of economic growth, predicted to add between $500 billion- $1.5 trillion in value to the global economy between 2018 and 2022, according to a report by Capgemini.

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Software, Low-Code App Development, Application Development Platform

How Artificial Intelligence Is Transforming Businesses

Article | June 15, 2023

Whilst there are many people that associate AI with sci-fi novels and films, its reputation as an antagonist to fictional dystopic worlds is now becoming a thing of the past, as the technology becomes more and more integrated into our everyday lives. AI technologies have become increasingly more present in our daily lives, not just with Alexa’s in the home, but also throughout businesses everywhere, disrupting a variety of different industries with often tremendous results. The technology has helped to streamline even the most mundane of tasks whilst having a breath-taking impact on a company’s efficiency and productivity

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The advances of AI in healthcare

Article | February 11, 2020

With the Government investing £250 million into the project, the Lab will consider how to use AI for the benefit of patients – whether this be the deployment of existing AI methods, the development of new technologies or the testing of their safety. Amongst other things, the initiative will aim to deliver earlier diagnoses of cancer. It is estimated that in excess of 50,000 extra patients could see their cancer being detected at an early stage, thus boosting survival rates. More specifically, a study has shown that AI is quicker in identifying brain tumour tissue than a pathologist.This would have a positive knock-on effect in other areas, such as enabling money to be saved (that otherwise would have been spent on further treatment) and reducing the workload of staff (at a time when there is a crisis in NHS workforce numbers).

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Spotlight

Mindteck

Mindteck, a global technology company established in 1991, provides Product Engineering solutions and Information Technology services to top-tier Fortune 100 companies, start-ups, leading universities and government entities. Its depth of knowledge and niche expertise in embedded systems and enterprise applications is complemented by dedicated Centers of Excellence in wireless design and storage testing.

Related News

AI Tech

AMD Enhances AI with Nod.ai Acquisition for Open-Source Solutions

AMD | October 11, 2023

AMD acquires Nod.ai to boost open-source AI solutions. AMD's Senior Vice President expects smoother AI deployment with Nod.AI. Nod.AI's SHARK software speeds up AI model deployment, in line with AMD's innovation focus. Advanced Micro Devices (AMD) has announced its definitive agreement to acquire Nod.ai, a leading open-source AI software expert. This strategic move is set to bolster AMD's open-source software strategy and expedite the deployment of optimized AI solutions on their high-performance platforms, including AMD Instinct data center accelerators, Ryzen AI processors, EPYC processors, Versal SoCs, and Radeon GPUs. The acquisition aligns with AMD's broader AI growth strategy, aiming to provide an open software ecosystem that simplifies AI model deployment for customers through developer tools, libraries, and models. Vamsi Boppana, senior vice president, Artificial Intelligence Group at AMD, reportedly remarked, The acquisition of Nod.ai is expected to significantly enhance our ability to provide AI customers with open software that allows them to easily deploy highly performant AI models tuned for AMD hardware. The addition of the talented Nod.ai team accelerates our ability to advance open-source compiler technology and enable portable, high-performance AI solutions across the AMD product portfolio. Nod.ai’s technologies are already widely deployed in the cloud, at the edge and across a broad range of end-point devices today. [Source – Globe Newswire] Nod.ai, known for delivering optimized AI solutions to top hyperscalers, enterprises, and startups, brings its SHARK software, which automates compiler-based optimization. This software minimizes the need for manual fine-tuning, reducing the time required to deploy high-performance AI models across a wide range of data center, edge, and client platforms utilizing AMD CDNA, XDNA, RDNA, and ‘Zen’ architectures. The acquisition reflects AMD's continuous commitment to innovation in high-performance computing, graphics, and visualization technologies. AMD seeks to provide adaptive products that cater to a broad range of industries and applications. It's important to note that this announcement includes forward-looking statements concerning the acquisition's expected benefits and is subject to certain risks and uncertainties. Investors are advised to review AMD's Securities and Exchange Commission filings for a detailed understanding of these risks and uncertainties. Acquiring open-source AI technology may introduce dependence on community support and expertise, potentially leading to security concerns and limited official assistance. Integrating the new software can also result in compatibility issues and market competition in the fiercely contested AI tech sector. However, the acquisition of Nod.ai enhances AMD's AI capabilities, streamlining the deployment of high-performance AI solutions. Embracing an open software strategy lowers entry barriers, and Nod.ai's automation reduces manual optimization needs, enabling deployment across diverse platforms while aligning with AMD's innovation focus.

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AI Tech

Microsoft's New Copilot: Enriching Windows Users with Advanced AI

Microsoft | September 22, 2023

Microsoft debuts Copilot, an advanced AI assistant for Windows PCs, enhancing tasks from text generation to organization, set to launch on September 26, 2023. Copilot integrates into Windows 11, Microsoft 365, Edge, and Bing, boosting productivity with real-time context while safeguarding user privacy. Concerns include data security and AI reliance, highlighting the necessity for a balanced approach to AI adoption. Microsoft has introduced a groundbreaking addition to its technology ecosystem with the launch of Copilot, a highly capable AI assistant designed to enhance the computing experience for Windows PC users. This advanced AI assistant offers a multifaceted approach to aiding users in their daily tasks, ranging from generating text and curating music playlists for concentration to facilitating window organization and assisting with creative pursuits involving photos and videos. What sets Copilot apart is its seamless integration of various AI tools that Microsoft has already deployed across different applications, offering users a unified and intuitive experience. Notably, Microsoft has leveraged OpenAI's ChatGPT technology to power Copilot, harnessing its robust capabilities to elevate user interactions. Yusuf Mehdi, Microsoft Consumer Chief Marketing Officer, reportedly commented, We are entering a new era of AI, one that is fundamentally changing how we relate to and benefit from technology. [Source – Yahoo News UK] Copilot's potential impact on the computing landscape is considerable. Its integration into Windows 11, Microsoft 365, Edge, and Bing represents a significant step toward a holistic AI companion that adapts to users' needs in real time, drawing insights from web context, work-related data, and current PC activities. This contextual awareness not only enhances productivity but also underscores Microsoft's commitment to user privacy and security. Copilot can be effortlessly summoned through app integration or via a right-click, making it an accessible and invaluable tool for users seeking to navigate the ever-evolving digital realm. However, it is essential to acknowledge that the proliferation of AI assistants like Copilot raises legitimate concerns. One prominent issue pertains to privacy and data security. While Microsoft emphasizes its commitment to safeguarding user information, the integration of AI assistants into various aspects of daily life necessitates stringent measures to protect sensitive data. Moreover, there is the challenge of potential over-reliance on AI, potentially leading to a decreased reliance on human problem-solving skills and creativity. Striking the right balance between AI assistance and human agency is a crucial consideration in the adoption of such technologies. In summary, Microsoft's Copilot represents a noteworthy advancement in the realm of AI-powered assistance for computing tasks. Its ability to unify various AI tools into a single, user-friendly experience holds immense promise for enhancing productivity and user engagement. However, as with any technological innovation, careful consideration of privacy, data security, and the potential implications of over-reliance on AI remains imperative in the quest for a seamless digital future.

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AI Tech, General AI, Software

DataRobot Announces New Generative AI Offering

Businesswire | August 11, 2023

DataRobot, the leader in Value-Driven AI, today announced a new generative AI offering, including platform capabilities and applied AI services, to accelerate the path from concept to value with generative AI. This offering uniquely brings both generative and predictive AI capabilities together in the DataRobot AI Platform, delivering an open and end-to-end solution for you to experiment, build, deploy, monitor and moderate enterprise-grade AI applications and assistants, and drive impact for your business. “We’ve talked to hundreds of customers looking to adopt generative AI who have concerns about existing tools on the market, including security and reputational risks, vendor lock-in and mounting technical debt from piecemeal solutions,” said Jay Schuren, Chief Customer Officer, DataRobot. “With over a decade at the forefront of AI innovation, we understand what it takes to deliver AI successfully and safely. Our new offering gives your teams everything they need to experiment quickly, deploy in production, monitor to ensure quality and ultimately get value from your generative AI projects.” The new offering builds on the DataRobot AI Platform to accelerate your generative AI initiatives by unifying best-in-class components and providing critical capabilities in an open and multi-cloud environment, including: - Generative AI Models Extended for the Enterprise: Seamlessly integrate large language models (LLMs), vector databases and prompting strategies with your enterprise data directly within DataRobot hosted notebooks. With a code-first experience and pre-built assistant recipes, you can rapidly develop customized solutions that meet your unique needs. - Enterprise-Grade Generative AI Observability: Gain confidence operating all of your generative and predictive AI assets with advanced monitoring, management and governance. Measure what matters, from operational and data drift metrics to generative AI-specific metrics like toxicity and truthfulness, and ensure applications stay “on-topic” using use case-specific guardrails. - Easy-to-Build Generative AI Applications: Quickly prototype, build and deploy end-to-end applications and assistants to deliver a complete generative AI powered experience to business stakeholders and end users with just a few lines of code, using a DataRobot-hosted Streamlit application sandbox. DataRobot is also introducing new generative AI services focused on end-to-end implementation of custom use cases as well as dedicated programming to upskill your workforce, designed and delivered by our applied AI experts: - Generative AI Training & Enablement for executives and practitioners, enabling leaders to quickly establish the level of generative AI proficiency that is necessary to remain competitive in today’s market. - Generative AI Ideation & Roadmapping Workshops for teams to go from use case ideation to implementation by systematically identifying and prioritizing high-value opportunities, and aligning leaders, data teams and stakeholders. - Generative AI Trust & Compliance Framework to support responsible generative AI governance processes and better prepare your business to meet existing guidelines and anticipate pending regulations. DataRobot supports customers from all industries to solve real-world business problems with generative and predictive AI. "The generative AI space is changing quickly, and the flexibility, safety and security of DataRobot helps us stay on the cutting edge with a HIPAA-compliant environment we trust to uphold critical health data protection standards," said Rosalia Tungaraza, AVP, Artificial Intelligence, Baptist Health South Florida. “We’re harnessing innovation for real-world applications, giving us the ability to transform patient care and improve operations and efficiency with confidence.” Connecting Ford Motor Company with over 3,800 Ford and Lincoln dealerships across the U.S. and Canada, FordDirect leverages the DataRobot AI Platform to better engage and anticipate customer needs. “DataRobot is an indispensable partner helping us maintain our reputation both internally and externally by deploying, monitoring, and governing generative AI responsibly and effectively,” said Tom Thomas, Vice President of Data Strategy, Analytics & Business Intelligence, FordDirect. “We are on the cusp of a major transition. Global organizations are excited about the possibilities to transform their businesses with generative AI while at the same time faced with risks ranging from hallucinations and toxicity, to governance and bias,” said Ritu Jyoti, Group Vice President, Worldwide Artificial Intelligence and Automation Research Practice Global AI Research Lead at IDC. “That’s why AI platforms like DataRobot are critical in unlocking business value with generative AI and predictive AI alongside robust monitoring, governance, and a broad ecosystem. They create a competitive edge for enterprises.” About DataRobot DataRobot is the leader in Value-Driven AI, a unique and collaborative approach to generative and predictive AI that combines an open platform, deep expertise and broad use-case experience to improve how organizations run, grow and optimize their business. The DataRobot AI Platform is the only complete AI lifecycle platform that interoperates with an organization’s existing investments in data, applications and business processes, and can be deployed on any cloud environment. Global organizations, including 40% of the Fortune 50, rely on DataRobot to drive greater impact and value from AI. Learn more at datarobot.com and follow us on LinkedIn and X (@DataRobot).

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AI Tech

AMD Enhances AI with Nod.ai Acquisition for Open-Source Solutions

AMD | October 11, 2023

AMD acquires Nod.ai to boost open-source AI solutions. AMD's Senior Vice President expects smoother AI deployment with Nod.AI. Nod.AI's SHARK software speeds up AI model deployment, in line with AMD's innovation focus. Advanced Micro Devices (AMD) has announced its definitive agreement to acquire Nod.ai, a leading open-source AI software expert. This strategic move is set to bolster AMD's open-source software strategy and expedite the deployment of optimized AI solutions on their high-performance platforms, including AMD Instinct data center accelerators, Ryzen AI processors, EPYC processors, Versal SoCs, and Radeon GPUs. The acquisition aligns with AMD's broader AI growth strategy, aiming to provide an open software ecosystem that simplifies AI model deployment for customers through developer tools, libraries, and models. Vamsi Boppana, senior vice president, Artificial Intelligence Group at AMD, reportedly remarked, The acquisition of Nod.ai is expected to significantly enhance our ability to provide AI customers with open software that allows them to easily deploy highly performant AI models tuned for AMD hardware. The addition of the talented Nod.ai team accelerates our ability to advance open-source compiler technology and enable portable, high-performance AI solutions across the AMD product portfolio. Nod.ai’s technologies are already widely deployed in the cloud, at the edge and across a broad range of end-point devices today. [Source – Globe Newswire] Nod.ai, known for delivering optimized AI solutions to top hyperscalers, enterprises, and startups, brings its SHARK software, which automates compiler-based optimization. This software minimizes the need for manual fine-tuning, reducing the time required to deploy high-performance AI models across a wide range of data center, edge, and client platforms utilizing AMD CDNA, XDNA, RDNA, and ‘Zen’ architectures. The acquisition reflects AMD's continuous commitment to innovation in high-performance computing, graphics, and visualization technologies. AMD seeks to provide adaptive products that cater to a broad range of industries and applications. It's important to note that this announcement includes forward-looking statements concerning the acquisition's expected benefits and is subject to certain risks and uncertainties. Investors are advised to review AMD's Securities and Exchange Commission filings for a detailed understanding of these risks and uncertainties. Acquiring open-source AI technology may introduce dependence on community support and expertise, potentially leading to security concerns and limited official assistance. Integrating the new software can also result in compatibility issues and market competition in the fiercely contested AI tech sector. However, the acquisition of Nod.ai enhances AMD's AI capabilities, streamlining the deployment of high-performance AI solutions. Embracing an open software strategy lowers entry barriers, and Nod.ai's automation reduces manual optimization needs, enabling deployment across diverse platforms while aligning with AMD's innovation focus.

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AI Tech

Microsoft's New Copilot: Enriching Windows Users with Advanced AI

Microsoft | September 22, 2023

Microsoft debuts Copilot, an advanced AI assistant for Windows PCs, enhancing tasks from text generation to organization, set to launch on September 26, 2023. Copilot integrates into Windows 11, Microsoft 365, Edge, and Bing, boosting productivity with real-time context while safeguarding user privacy. Concerns include data security and AI reliance, highlighting the necessity for a balanced approach to AI adoption. Microsoft has introduced a groundbreaking addition to its technology ecosystem with the launch of Copilot, a highly capable AI assistant designed to enhance the computing experience for Windows PC users. This advanced AI assistant offers a multifaceted approach to aiding users in their daily tasks, ranging from generating text and curating music playlists for concentration to facilitating window organization and assisting with creative pursuits involving photos and videos. What sets Copilot apart is its seamless integration of various AI tools that Microsoft has already deployed across different applications, offering users a unified and intuitive experience. Notably, Microsoft has leveraged OpenAI's ChatGPT technology to power Copilot, harnessing its robust capabilities to elevate user interactions. Yusuf Mehdi, Microsoft Consumer Chief Marketing Officer, reportedly commented, We are entering a new era of AI, one that is fundamentally changing how we relate to and benefit from technology. [Source – Yahoo News UK] Copilot's potential impact on the computing landscape is considerable. Its integration into Windows 11, Microsoft 365, Edge, and Bing represents a significant step toward a holistic AI companion that adapts to users' needs in real time, drawing insights from web context, work-related data, and current PC activities. This contextual awareness not only enhances productivity but also underscores Microsoft's commitment to user privacy and security. Copilot can be effortlessly summoned through app integration or via a right-click, making it an accessible and invaluable tool for users seeking to navigate the ever-evolving digital realm. However, it is essential to acknowledge that the proliferation of AI assistants like Copilot raises legitimate concerns. One prominent issue pertains to privacy and data security. While Microsoft emphasizes its commitment to safeguarding user information, the integration of AI assistants into various aspects of daily life necessitates stringent measures to protect sensitive data. Moreover, there is the challenge of potential over-reliance on AI, potentially leading to a decreased reliance on human problem-solving skills and creativity. Striking the right balance between AI assistance and human agency is a crucial consideration in the adoption of such technologies. In summary, Microsoft's Copilot represents a noteworthy advancement in the realm of AI-powered assistance for computing tasks. Its ability to unify various AI tools into a single, user-friendly experience holds immense promise for enhancing productivity and user engagement. However, as with any technological innovation, careful consideration of privacy, data security, and the potential implications of over-reliance on AI remains imperative in the quest for a seamless digital future.

Read More

AI Tech, General AI, Software

DataRobot Announces New Generative AI Offering

Businesswire | August 11, 2023

DataRobot, the leader in Value-Driven AI, today announced a new generative AI offering, including platform capabilities and applied AI services, to accelerate the path from concept to value with generative AI. This offering uniquely brings both generative and predictive AI capabilities together in the DataRobot AI Platform, delivering an open and end-to-end solution for you to experiment, build, deploy, monitor and moderate enterprise-grade AI applications and assistants, and drive impact for your business. “We’ve talked to hundreds of customers looking to adopt generative AI who have concerns about existing tools on the market, including security and reputational risks, vendor lock-in and mounting technical debt from piecemeal solutions,” said Jay Schuren, Chief Customer Officer, DataRobot. “With over a decade at the forefront of AI innovation, we understand what it takes to deliver AI successfully and safely. Our new offering gives your teams everything they need to experiment quickly, deploy in production, monitor to ensure quality and ultimately get value from your generative AI projects.” The new offering builds on the DataRobot AI Platform to accelerate your generative AI initiatives by unifying best-in-class components and providing critical capabilities in an open and multi-cloud environment, including: - Generative AI Models Extended for the Enterprise: Seamlessly integrate large language models (LLMs), vector databases and prompting strategies with your enterprise data directly within DataRobot hosted notebooks. With a code-first experience and pre-built assistant recipes, you can rapidly develop customized solutions that meet your unique needs. - Enterprise-Grade Generative AI Observability: Gain confidence operating all of your generative and predictive AI assets with advanced monitoring, management and governance. Measure what matters, from operational and data drift metrics to generative AI-specific metrics like toxicity and truthfulness, and ensure applications stay “on-topic” using use case-specific guardrails. - Easy-to-Build Generative AI Applications: Quickly prototype, build and deploy end-to-end applications and assistants to deliver a complete generative AI powered experience to business stakeholders and end users with just a few lines of code, using a DataRobot-hosted Streamlit application sandbox. DataRobot is also introducing new generative AI services focused on end-to-end implementation of custom use cases as well as dedicated programming to upskill your workforce, designed and delivered by our applied AI experts: - Generative AI Training & Enablement for executives and practitioners, enabling leaders to quickly establish the level of generative AI proficiency that is necessary to remain competitive in today’s market. - Generative AI Ideation & Roadmapping Workshops for teams to go from use case ideation to implementation by systematically identifying and prioritizing high-value opportunities, and aligning leaders, data teams and stakeholders. - Generative AI Trust & Compliance Framework to support responsible generative AI governance processes and better prepare your business to meet existing guidelines and anticipate pending regulations. DataRobot supports customers from all industries to solve real-world business problems with generative and predictive AI. "The generative AI space is changing quickly, and the flexibility, safety and security of DataRobot helps us stay on the cutting edge with a HIPAA-compliant environment we trust to uphold critical health data protection standards," said Rosalia Tungaraza, AVP, Artificial Intelligence, Baptist Health South Florida. “We’re harnessing innovation for real-world applications, giving us the ability to transform patient care and improve operations and efficiency with confidence.” Connecting Ford Motor Company with over 3,800 Ford and Lincoln dealerships across the U.S. and Canada, FordDirect leverages the DataRobot AI Platform to better engage and anticipate customer needs. “DataRobot is an indispensable partner helping us maintain our reputation both internally and externally by deploying, monitoring, and governing generative AI responsibly and effectively,” said Tom Thomas, Vice President of Data Strategy, Analytics & Business Intelligence, FordDirect. “We are on the cusp of a major transition. Global organizations are excited about the possibilities to transform their businesses with generative AI while at the same time faced with risks ranging from hallucinations and toxicity, to governance and bias,” said Ritu Jyoti, Group Vice President, Worldwide Artificial Intelligence and Automation Research Practice Global AI Research Lead at IDC. “That’s why AI platforms like DataRobot are critical in unlocking business value with generative AI and predictive AI alongside robust monitoring, governance, and a broad ecosystem. They create a competitive edge for enterprises.” About DataRobot DataRobot is the leader in Value-Driven AI, a unique and collaborative approach to generative and predictive AI that combines an open platform, deep expertise and broad use-case experience to improve how organizations run, grow and optimize their business. The DataRobot AI Platform is the only complete AI lifecycle platform that interoperates with an organization’s existing investments in data, applications and business processes, and can be deployed on any cloud environment. Global organizations, including 40% of the Fortune 50, rely on DataRobot to drive greater impact and value from AI. Learn more at datarobot.com and follow us on LinkedIn and X (@DataRobot).

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