How is AI helping Researchers Identify a New Class of Antibiotic?

To combat diseases caused by bacteria that are resistant to many antibiotics, artificial intelligence has been essential in the discovery of a new class of medications. This may be useful in the fight against antibiotic resistance, which is a growing problem that killed over 1.2 million people in 2019 and will likely continue to do so for decades to come. A novel antibiotic that can kill a type of bacterium responsible for many drug-resistant diseases has been identified by researchers at MIT and McMaster University using an artificial intelligence algorithm.

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The medicine has the potential to battle Acinetobacter baumannii, a type of bacteria commonly found in healthcare facilities and a cause of pneumonia, meningitis, and other severe diseases if it were to be developed for use in patients. Wounds sustained by troops serving in Iraq and Afghanistan are also frequently infected with this particular bacterium. Using a machine-learning model they trained to determine if a chemical compound inhibits the growth of A. baumannii, the researchers were able to identify the novel medicine from a library of roughly seven thousand potential medicinal molecules.

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What are its features?

While very few new antibiotics have been created during the past several decades, many pathogenic bacteria have grown progressively resistant to current ones.

Collins, Stokes, and Regina Barzilay, a professor at MIT and co-author of the current paper, set out a few years ago to tackle this increasing problem using machine learning, an AI technique that can learn to identify patterns in massive datasets. Collaborating with MIT’s Abdul Latif Jameel Clinic for Machine Learning in Health, Collins and Barzilay intended to find novel medicines with structurally distinct molecular bonds using this method.

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First, they showed that they could train a machine-learning system to find chemical compounds that could stop E. coli from growing. The researchers named the molecule halicin after the fictitious AI system from “2001: A Space Odyssey.” The algorithm produced it from a screen of over 100 million molecules. In addition to killing E. coli, they demonstrated that this chemical might eradicate other treatment-resistant bacterial species. After training the algorithm, scientists fed it data from the Broad Institute’s Drug Repurposing Hub, which included 6,680 novel molecules. A few hundred high-quality results were produced by this analysis, which did not take more than two hours. Researchers focused on compounds with structures different from current antibiotics or molecules from the training data, choosing 240 to test experimentally in the lab.

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A New Class of Antibiotic Candidates That Can Kill a Drug-Resistant Bacterium

Nine antibiotics, including a highly effective one, were produced during those tests. This chemical, which was first investigated for its use as a diabetes medication, was found to be highly efficient against A. baumannii but inactive against other bacterial species such as Pseudomonas aeruginosa, Staphylococcus aureus, and carbapenem-resistant Enterobacteriaceae.

Antibiotics are highly prized for their “narrow spectrum” killing capabilities, which reduces the likelihood of bacteria quickly developing resistance to the medicine. A further perk is that the medicine will probably not harm the good bacteria already present in the human digestive tract, which helps to prevent opportunistic illnesses like Clostridium difficile.David Braley Center for Antibiotic Discovery, Weston Family Foundation, Audacious Project, C3.ai Digital Transformation Institute, Abdul Latif Jameel Clinic for Machine Learning in Health, DARPA Accelerated Molecular Discovery, Canadian Institutes of Health Research, Genome Canada, McMaster University’s Faculty of Health Sciences, Boris Family, a Marshall Scholarship, and the Department of Energy Biological and Environmental Research program were among the organizations that contributed to the funding of this research.

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Polycrystalline materials are utilized extensively in information equipment, solar cells, and electronic devices; however, these materials can experience a decrease in efficiency due to tiny flaws known as dislocations. To better understand these defects, researchers at Japan’s Nagoya University utilized artificial intelligence. Advanced Materials was the publication that carried out the research.

The production of microscopic crystal flaws due to stress and temperature variations is a big issue with employing polycrystals in industrial applications. A disruption to the normal arrangement of atoms in the lattice can impact electrical conduction and overall performance; these are known as dislocations. It is critical to comprehend the production of these dislocations to lessen the likelihood of failure in devices that employ polycrystalline materials.

Using a novel AI, a group of researchers from Nagoya University, headed by Professor Noritaka Usami and comprising Lecturer Tatsuya Yokoi, Associate Professor Hiroaki Kudo, and others, analyzed picture data of polycrystalline silicon, a material commonly utilized in solar panels. With the use of the AI’s virtual 3D model, the team was able to pinpoint exactly where the material’s performance was being negatively impacted by dislocation clusters. This research may have significant theoretical and practical consequences for our understanding of crystal development and deformation. An important theoretical framework for understanding the behavior of dislocations in materials is the Haasen-Alexander-Sumino (HAS) model. However, according to Usami, they have found dislocations that the Haasen-Alexander-Sumino model failed to capture.

Unexpectedly substantial tensile bond strains along the border of the staircase-like structures that prompted dislocation production were discovered shortly after when the scientists computed the arrangement of the atoms in these structures, which was another surprise.

Electron Microscopy and Theoretical Computations

With the use of the AI’s virtual 3D model, the team was able to pinpoint exactly where the material’s performance was being negatively impacted by dislocation clusters. Researchers employed electron microscopy and theoretical computations to deduce the formation mechanisms of the dislocation clusters after their locations had been identified.
The study, published in Advanced Materials, titled “Multicrystalline Informatics Applied to Multicrystalline Silicon for Unraveling the Microscopic Root Cause of Dislocation Generation,” delves into these questions.

Professor Noritaka Usami oversaw the study of polycrystalline materials, which also involved Lecturer Tatsuya Yokoi, Associate Professor Hiroaki Kudo, and others. They analyzed picture data of polycrystalline silicon, a material commonly used in solar panels, using a novel AI. The team was able to pinpoint the regions where dislocation clusters were impacting the performance of polycrystalline materials thanks to the AI’s creation of a virtual 3D model. Researchers employed electron microscopy and theoretical computations to deduce the formation mechanisms of the dislocation clusters after their locations had been identified.

At the grain boundaries, they discovered staircase-like structures and showed stress distribution in the crystal lattice. During crystal development, these structures seem to induce dislocations. In sum, the study should help in the development of new polycrystalline materials and shed light on the way to creating universal standards for high-performance materials.

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As we embark on the financial landscape of 2023, Mastercard takes center stage with a series of groundbreaking developments that reshape the future of digital payments and financial technology. Mastercard, a global leader in payment solutions, kicks off the year 2023 with a slew of transformative news stories, highlighting its pivotal role in driving innovation and shaping the way we conduct transactions.

In the dynamic world of finance, Mastercard stands as a beacon of innovation, and the top 10 news stories for the year 2023 offer a glimpse into the company’s strategic maneuvers and technological advancements. As the digital economy continues to thrive, Mastercard unveils a tapestry of significant news in 2023, showcasing its commitment to revolutionizing the way we approach payments, security, and financial inclusion.

From cutting-edge advancements in contactless technology to strategic partnerships fostering financial inclusivity, Mastercard’s top 10 news stories for 2023 encapsulate a narrative of progress and adaptability in the ever-evolving realm of global finance.

Top 10 News of Mastercard in 2023

Dynamic Yield by Mastercard Unveils Shopping Muse, the Next Generation Personal Retail Assistant

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In the heart of the tech revolution, Nvidia shines as a beacon of innovation in 2023, unveiling a host of news stories that redefine the landscape of graphics processing and artificial intelligence. Nvidia, a powerhouse in the world of GPUs and AI computing, kicks off the year 2023 with a series of groundbreaking announcements, signaling its continued dominance in the forefront of cutting-edge technologies.

As the demand for high-performance computing grows, Nvidia’s top 10 news stories for 2023 showcase the company’s relentless pursuit of excellence, from the latest GPU architectures to breakthroughs in AI research. Stepping into the future, Nvidia’s 2023 narrative unfolds with a tale of technological leaps, strategic partnerships, and advancements that solidify its position as a driving force in the realms of gaming, data centers, and artificial intelligence.

From revolutionary graphics cards to breakthroughs in quantum computing, Nvidia’s journey in 2023 is a story of constant innovation, shaping industries and pushing the boundaries of what’s possible in the world of computing.

Top 10 News of Nvidia in 2023

NVIDIA Isaac Sim And AWS

With the upcoming arrival of NVIDIA Isaac Sim and NVIDIA L40S GPUs to Amazon Web Services, programmers will be able to create and launch cloud-based apps for accelerated robotics. Developed on the NVIDIA Omniverse platform for creating and linking OpenUSD applications, Isaac Sim is an extendable simulator for AI-enabled robotics. The L40S GPU is designed to handle the upcoming wave of data center workloads with its advanced AI computing, graphics, and media acceleration capabilities.

Among the AWS early users of the Isaac Sim platform are Theory Studios, Amazon Robotics, and Soft Robotics. Applications of artificial intelligence (AI) in robotics are trained and tested using robotics simulation. Virtual advancements are reaching new heights thanks to simulations powered by synthetic data. Before operation, simulations may be used to check, validate, and optimize robot designs, systems, and algorithms. In addition to minimizing expensive production change orders, it may improve facility designs before construction or modification to achieve optimal efficiency.

NVIDIA Brings Business Intelligence to Chatbots, Copilots and Summarization Tools With Enterprise-Grade Generative AI Microservice

AWS re:Invent NVIDIA announced a generative AI microservice that lets enterprises connect custom large language models to enterprise data to deliver highly accurate responses for their AI applications.

NVIDIA NeMo™ Retriever — a new offering in the NVIDIA NeMo family of frameworks and tools for building, customizing and deploying generative AI models — helps organizations enhance their generative AI applications with enterprise-grade retrieval-augmented generation (RAG) capabilities.

“Generative AI applications with RAG capabilities are the next killer app of the enterprise,” said Jensen Huang, founder and CEO of NVIDIA. “With NVIDIA NeMo Retriever, developers can create customized generative AI chatbots, copilots and summarization tools that can access their business data to transform productivity with accurate and valuable generative AI intelligence.”

Lenovo and NVIDIA Announce Hybrid AI Solutions to Help Enterprises Quickly Adopt GenAI

Lenovo and NVIDIA announced an expansion of their partnership with new, hybrid solutions and engineering collaboration that supports their shared vision to bring the power of generative AI to every enterprise

In close collaboration with NVIDIA, Lenovo will deliver fully integrated systems that bring AI-powered computing to everywhere data is created, from the edge to the cloud, helping businesses easily deploy tailored generative AI applications to drive innovation and transformation across any industry.

“With generative AI driving the greatest technology transformation of our time, enterprises are seeking solutions that give them the flexibility to develop and deploy workloads across their workstations, data centers and clouds,” said Bob Pette, Vice President of Enterprise Platforms at NVIDIA. “NVIDIA and Lenovo are providing a comprehensive portfolio of hybrid AI systems that businesses can rely on to power generative AI from virtually anywhere.”

NVIDIA Redefines Workstations to Power New Era of AI, Design, Industrial Metaverse

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Lenovo, a global tech powerhouse, takes center stage in 2023 with a cascade of exciting news stories that underscore its continued influence in the ever-evolving world of technology. Embarking on the journey of a new year, Lenovo sets the tone with a series of top-tier developments, positioning itself at the forefront of innovation and progress in 2023.

In the fast-paced landscape of consumer electronics, Lenovo’s top 10 news stories for 2023 unfold as a tapestry of advancements, collaborations, and strategic moves, reflecting the company’s commitment to staying ahead in the competitive tech market. As the digital era progresses, Lenovo showcases its prowess with a collection of transformative narratives, ranging from cutting-edge product launches to strategic partnerships that redefine the boundaries of technological possibilities.

Lenovo’s 2023 story is one of resilience and innovation, where each news headline paints a picture of a company determined to shape the future of computing and redefine the user experience.

Top 10 News of Lenovo in 2023

Lenovo Introduces Feature-Packed Devices and Solutions at CES that Deliver Users a More Personalized Experience

Lenovo Launches New Hybrid Cloud Platforms and Services to Accelerate AI

Lenovo announced it has expanded its hybrid cloud platform for AI with new ThinkAgile hyperconverged solutions and ThinkSystem servers that advance cloud deployment, hybrid connectivity and AI capabilities, powered by the next generation of Intel® Xeon® Scalable Processors. The new AI ready platform delivers improved performance and the latest accelerators as a critical next step for delivering a dynamic hybrid AI approach across public, private, and foundational models to enable AI for All.

The new Lenovo ThinkAgile hybrid cloud solutions are engineered to boost AI performance and build cloud agility by delivering more compute and faster memory to its market-leading portfolio when and where it is needed. Additionally, Lenovo Professional Services for AI and TruScale as-a-service offerings help customers simplify IT and accelerate AI with new integrated hybrid cloud for edge capabilities that quickly help businesses grow and only pay for what they need.

Lenovo Unveils New Data Management Solutions to Enable AI Workloads

 Lenovo announced its next wave of data management innovation with new ThinkSystem DG Enterprise Storage Arrays and ThinkSystem DM3010H Enterprise Storage Arrays, designed to make it easier for organizations to enable AI workloads and unlock value from their data. Also announced are two new integrated and engineered ThinkAgile SXM Microsoft Azure Stack solutions, enabling a unified hybrid cloud solution for seamless data management. As businesses continue to scale their operations to address growing data, security and sustainability requirements, the new Lenovo flash solutions provide customers with an accelerated path to deploy AI workloads efficiently and with added security features from edge to cloud, enabling workload consolidation and mobilizing faster insights fortified with ransomware protection.

Lenovo Grows AI Infrastructure Revenue to Over US$2 Billion and Brings AI to the Data

• Lenovo simplifies deployment for businesses with additional US$1 billion investment in portfolio expansion and one-stop enablement wherever data resides, from the pocket to the cloud

• Lenovo AI Innovators program delivers 150+ turnkey solutions, helping businesses implement generative AI, immersive metaverse simulations and cognitive decisions at scale

• Expanded AI-ready portfolio of smart devices and edge-to-cloud infrastructure includes new Lenovo ThinkEdge and ThinkSystem platforms purpose-built for enabling AI workloads

Lenovo Launches Digital Workplace Solutions to Boost Employee Experience and Increase Productivity

Hybrid work styles preferred by employees create security and other workplace challenges that distract leaders from the core business 

• End-to-end Lenovo support, guidance and managed services create competitive advantages from hybrid workforce/workplace challenges

• Lenovo DWS helps companies improve operational cost, enhance productivity and improve security posture through end-to-end services built on a state-of-the-art platform and deep expertise in technology

At a time when companies are struggling to find customized technologies to address their unique business requirements, Lenovo Solutions and Services Group (SSG) is launching Digital Workplace Solutions (DWS), a new managed services portfolio of intelligent tools and systems. DWS delivers work-related technology, security, efficiency, and employee satisfaction so that executives can deliver on key performance outcomes.

Lenovo Unveils Next Generation of Intel-Based Smart Infrastructure Solutions to Accelerate IT Modernization

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Vision-Based Speed Detection Algorithms

There are at least two primary reasons why it is becoming more and more crucial to precisely estimate the speed of road vehicles. To start, there has been a noticeable uptick in the number of speed cameras deployed around the globe in recent years. This is likely due to the widespread belief that enforcing reasonable speed limits is a great way to make roads safer for everyone. In addition, smart cities rely heavily on traffic monitoring and forecasting in road networks to improve traffic, pollution, and energy consumption.

One of the most important metrics for traffic conditions is vehicle speed. There are a lot of obstacles to overcome with vision-based systems when it comes to accurate vehicle speed detection, but there are also a lot of potential benefits, like a significant drop in costs (because range sensors aren’t needed) and the ability to correctly identify vehicles.

Video camera input data is the foundation of vision-based speed detection algorithms. There will be a photo album starting with the initial reveal and ending with the final reveal for every car. Factors such as vehicle speed, focus length, frame rate, and camera orientation relative to the road determine the total number of usable photographs.

Features:

• Variously known as traffic surveillance cameras or traffic CCTV, traffic cameras record traffic events live. Automatic or manual (visible inspection by a human operator) traffic flow, congestion, and accident monitoring is possible with their help. These cameras are often infrastructure- or drone-based and set up at a distance from the flow of traffic.
• Cams that record vehicles’ speeds are often called traffic enforcement cameras. In common parlance, they are a tool for keeping tabs on cars’ speeds apart from the actual speed sensor (be it radar, laser, or vision). The word “camera” comes from the fact that any system that uses radar or lasers to capture images of the vehicle also uses a camera. The word “speed camera” is used here in its most basic sense, meaning systems that measure speed using vision. Compared to the traffic cameras, their placement is typically more advantageous.

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Cornell and Open University of the Netherlands scholars have developed a programmable network model to modernize the internet’s architecture through software-defined networks. This model allows researchers and network administrators to customize packet scheduling, the air traffic control mechanism built into network switches. The research team focused on the network switch, which powers networks and the internet, to design the next generation of networking hardware-software.

Small pizza box-sized switches govern network data flow and connect devices to a computer network. They schedule packets, which routes data through a network. The switch processes data from thousands of network users, including emails, news site visits, and Zoom calls. The switch’s packet scheduler prioritizes and arranges data clusters according on network manager policies. Finally, the switch forwards packets to nearby switches until they reach the end user’s device.

Researchers claimed changing this air traffic control procedure has been impossible because manufacturers encode scheduling specifications into the switch. Once placed in new network switches, the team’s methodology would allow network administrators to customize the switch’s packet-scheduling software, building on MIT and Stanford researchers’ 2016 solution.

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One may make the case that creators, authors, and artists should have some say over who uses and profits from their work. This is typically accomplished via copyright laws. In most cases, the legal notion of “individual intellectual effort” is used by these statutes to establish authorship. In other words, the artist must have infused their work with sufficient originality and imagination to set it apart from previous works. But how can a person accomplish this? Some contend that, in contrast to AI, humans possess a unique quality that enables us to produce “new” works of art.

The IP battle between humans and AI

When it comes to intellectual property law, many jurisdictions have ruled that only “real humans” can be inventors, creators, or authors. However, when AI is involved, it’s not always apparent who is regarded as the author of a piece. Currently popular generative AI solutions take text suggestions as input and output what the user wants. Did a human put in enough labor to be deemed the author, inventor, or creator of the output work when they entered a specific set of prompts into an AI tool? In such case, where did the creative energy and originality originate from if the work is not plagiarized?

Many issues arise for those making and utilizing these technologies as a result of this line of thinking, particularly when trying to establish ownership. Generally speaking, it’s bad for the IP system as a whole. What, however, happens when an AI tool reaches the point where it is as knowledgeable as a human and has accumulated all the facts and experiences that a human could ever have? Similar to how a chess computer can anticipate every possible move a grandmaster would make, the AI would be capable of solving every difficulty that a person might think of. As a result, practically no new ideas are generated today, unless the human creator possesses exclusive, non-disclosable data.

Avoiding intellectual property problems with generative AI

You can take immediate, actionable actions to guarantee that anything created with the aid of generative AI will be credited to you as the creator, author, or inventor. The most critical thing is to keep track of when and how you employ AI technologies, as well as the data you use to obtain results. The newest generation of AI tools require you to document the prompts you use, together with the date and version of the tool, so they can be properly tracked. This might be very important later on when you need to prove that you were the rightful creator or inventor by demonstrating that enough “intellectual effort” was put into it.

It is important to ensure that you possess adequate rights to the datasets utilized for training new AI tools before beginning development. By doing so, you may rest assured that your tool’s underlying AI model will not mistakenly generate derivative works that violate the rights of others. The number of governments mandating the sharing of training datasets is expected to grow over time.

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What AI can’t do is replace the natural ‘gut feel’ of a healthcare professional.

Smart Use of Artificial Intelligence in Health Care- How Robots are Helping Doctors?

With the help of AI, telemedicine and RPM may provide patients with up-to-the-minute health information. To guarantee ethical AI use, legislative frameworks, and ethical concerns have come to the fore. Instead of seeing AI as a replacement for human healthcare providers, the focus is on how AI systems may work in tandem with them. The picture highlights the revolutionary integration of AI into several aspects of healthcare, which holds great promise for better diagnoses, personalized treatments, and overall patient care.

By 2024, artificial intelligence is expected to make great strides in the medical field. Deep learning algorithms improve the accuracy of X-ray, MRI, and CT scan interpretation, which is useful in medical imaging and diagnostics. AI plays a crucial role in the drug discovery process by sifting through large datasets in search of promising compounds and automating development. Using a patient’s unique genetic and molecular profile, personalized medicine employs AI to create individualized treatment plans. Using natural language processing to glean insights from unstructured clinical data, predictive analytics helps with patient outcome prediction and at-risk population management.

The research examines six key areas where AI directly affects the patient and three sectors of the healthcare value chain that might gain from more scaling of AI. It also looks at specific instances of current AI solutions in healthcare.

The increase in investments isn’t surprising, as 90% of the healthcare leaders surveyed believe that AI initiatives are important for their organizations to remain competitive in the market. When asked about their organization’s approach to technology innovation, 80% self-reported that they are either edge experimenters (organizations that tend to be first adopters of new technology or first to try new approaches and test unknown use cases) or fast followers (organizations that typically are next in line to adopt after some experimentation).

Robots Cannot Substitute Doctors!

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In the ever-evolving digital landscape, Google stands as a juggernaut of innovation, and as we delve into 2024, the tech giant unveils a compelling narrative with its top 10 news stories—each a testament to its influence in shaping the future of technology. Google, the omnipresent force in the world of search engines, cloud computing, and artificial intelligence, sets the stage for 2023 with a series of groundbreaking developments that transcend conventional boundaries.

As the tech titan continues to redefine the way we interact with information, Google’s top 10 news stories for 2023 offer a glimpse into the company’s bold strides in areas ranging from AI research and quantum computing to sustainability and beyond.

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Top 10 News of Google in 2023

Google’s New LLM- MedLM

Google has introduced MedLM, a set of healthcare-specific foundation models, and is now offering it to some US-based Google Cloud clients through the Vertex AI platform. At the moment, two models are constructed using Med-PaLM 2 under MedLM.

New to the Google ecosystem is MedLM, a collection of artificial intelligence models developed specifically for use in healthcare. The Vertex AI platform will make MedLM, which is based on Google’s medical domain large language model (LLM) Med-PaLM 2, available to Google Cloud customers in the US. Google states that MedLM was developed via extensive testing and partnerships with global healthcare organizations.

To improve patient access, experience, and outcomes, Google is partnering with Accenture to use generative AI. Healthcare firms may improve patient outcomes by combining MedLM with Google Cloud’s Claims Acceleration Suite. Deloitte and Google Cloud are collaborating on a pilot program called MedLM to help contact center agents find the best providers for their clients by making it easier to get information from provider directories and benefits paperwork.

Introducing A Benchmark Model Gemini By Google

Last Words

Navigating the complexities of the digital age, Google’s narrative for the year unfolds with a mosaic of transformative news, showcasing its commitment to pushing the boundaries of technology and addressing the evolving needs of a global audience. From cutting-edge advancements in machine learning to strategic initiatives in privacy and user experience, Google’s journey in 2023 is characterized by a series of pivotal moments that underscore its role as an industry leader and innovator.

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