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Analyticsindiamag
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TSMC, NVIDIA in Talks for AI Chip Production in Arizona
- Taiwan Semiconductor Manufacturing Co. (TSMC) is in talks with NVIDIA to produce its Blackwell AI chips at its Arizona facility.
- TSMC's Arizona plant, expected to start production in 2024, would handle the front-end process of Blackwell chip production.
- NVIDIA's Blackwell chips are in high demand for generative AI and accelerated computing applications.
- The talks highlight the growing role of TSMC's Arizona plant in meeting global demand for advanced AI chips.
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Analyticsindiamag
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Former PayPal COO David Sacks Appointed as US AI, Crypto Czar
- David Sacks, former PayPal COO, has been appointed as the United States' first Artificial Intelligence and Crypto Czar.
- Sacks will work closely with Elon Musk to establish a legal framework for the cryptocurrency industry and ensure American competitiveness in AI and crypto.
- Sacks will serve as a special government employee, working up to 130 days per year, and act as a liaison between the crypto industry, Congress, and federal agencies.
- The AI and Crypto Czar will provide regulatory clarity for the crypto sector and guide policy for AI adoption.
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Analyticsindiamag
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Why is No One Talking About Adversarial Machine Learning?
- Adversarial Machine Learning (AML) refers to techniques that are used to exploit the weaknesses of Machine Learning (ML) models creating subtle perturbations in input data to deceive these systems.
- AML can become tools for attackers facilitating sophisticated and automated attacks such as phishing and malware threats.
- AML is a bit difficult to detect as attackers use ML to disrupt machines learning models through techniques like model poisoning, model theft, and adversarial inputs.
- Several possible threats can occur at the Model Deployment Stage such as Evasion Attacks, Poisoning Attacks, Model Extraction Attacks, and Inference Attacks.
- The importance of securing AI systems at every stage of their lifecycle from data collection to building models to deployment is crucial.
- By proactively addressing these challenges, we can ensure AI systems remain trustworthy and reliable.
- Introducing adversarial examples during the training phase can help models learn to resist attacks.
- Continuous vulnerability assessments and penetration testing can identify potential weaknesses in AI systems.
- Building interpretable models allows developers to identify and address unexpected behaviours more effectively.
- Organisations must prioritise security as a foundational element of AI development, not an afterthought.
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Medium
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Your First 30 Days as a Data Engineer: The Reality Check!
- Data Engineers joining a new team often have to navigate existing complexities rather than creating something new.
- In the first month, the focus should be on learning and understanding the current systems and stakeholders' needs.
- Common myths include building data pipelines and transforming raw data, while the reality involves dealing with data discrepancies and inconsistencies.
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Analyticsindiamag
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Google Partners with Andhra Pradesh Govt to Drive AI Initiatives
- Google partners with Andhra Pradesh Govt to drive AI initiatives.
- Google signs MoU with the government to implement AI solutions in sectors like healthcare and environmental sustainability.
- Initiatives include AI skills development, fostering startups, and improving healthcare outcomes.
- Google to provide AI training, mentorship, and access to startups and introduce AI-powered tools for healthcare and sustainability.
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Dev
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Ceres Search
- Part 1: Advent of Code 2024 Day 4 involves finding 'X' in a grid and walking three steps in eight directions from each 'X' creating a word. Solution involves cataloguing the coordinates of each 'X',checking each direction for the spelling of 'XMAS'.
- Part 2: Advent of Code 2024 Day 4 involves finding 'M' in a grid and looking the configuration of a 5-cell phrase, MSSM, MMSS, SMMS, or SSMM, diagonally adjacent to 'A'. Solution involves finding every 'A', setting Stringified coordinates for each match and checking the four cells.
- The JavaScript coding of the strategy covered the padding of the grid with a 3-cell thick border, all eight relative coordinates, as well as the algorithm for both parts of the whole question.
- The author ultimately got the faster solution by using As instead of Ms in Part 2 and thanked the creator of the puzzle for another fun and challenging puzzle.
- The problem involves grid puzzles which often suffer the obstacle of out-of-bounds indices. The author overcame this obstacle by using a 3-cell thick border for padding and opting for #2 strategies.
- The typical approach to padding in grid puzzles is either adding checks to break the condition for non - existent rows or columns or padding the grid with enough rows and columns that there is no risk of going out-of-bounds.
- A successful approach to Part 1 involves: finding the index of each 'X' in the grid, for each 'X', checking the next three letters in eight directions, and if the path ends up spelling 'XMAS', adding one to a running total.
- In Part 2 of Advent of Code 2024 Day 4,using the 'A' alphabet instead and checking four cells diagonally adjacent to it gives the pattern for X-MAS matches.
- The author's strategy was to find every 'A',check each one in a clockwise, and then check if the letters spell 'XMAS'.
- The solution to Advent of Code 2024 Day 4 involves building the Set() of Stringified coordinates for each match to only account for an X-MAS instance once. Author credits usage of Word Search Puzzles strategy for this task.
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Analyticsindiamag
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AI’s Material ‘Breakthroughs’ are Still Useless
- Orbital Materials is creating new materials to decarbonise Amazon's data centres using their proprietary AI platform.
- Orbital claims using AI has improved the speed of material discover 10 times faster than traditional methods.
- Meta recently released a colossal dataset called Open Materials 2024, containing over 118 million examples of material simulations and structures.
- The numbers speak for themselves. The next time it seems exciting when AI has discovered new materials, it’s time to give ourselves a reality check.
- When Google Deepmind made the announcement last year, the company did not take long for contradictory results to come into the picture.
- Moreover, newly discovered materials need to go through a lot of testing, and the world has seen quite a few tragedies when they’re put out in the real world.
- From analysing the materials’ failure modes in controlled conditions to setting up an industrial-scale factory, following regulations, and justifying the choices to investors and customers, one is surely set to turn into Sisyphus.
- Deep learning has amplified materials research and discovery for a few years now. However, if there’s one way AI can save humanity, it lies in not just discovering new materials, but also finding ways to synthesise and manufacture them in commercial capabilities.
- Google DeepMind released research titled ‘Scaling deep learning for material discovery’ discovering 380,000 materials, but many materials discovered weren’t truly novel.
- Orbital plans to test carbon removal technologies by the end of 2025.
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Analyticsindiamag
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OpenAI Sells $200 ChatGPT Pro with Dad Jokes—Who’s Buying?
- OpenAI has released the full version of o1 and introduced a new $200 ChatGPT Pro model.
- o1 is the flagship model capable of handling multimodal inputs and reading content from images.
- The ChatGPT Pro plan includes all features of the Plus plan and provides access to the o1 Pro mode.
- OpenAI has demonstrated improved performance and announced new developer-centric features.
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Medium
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Revolutionizing Digital Marketing: The World’s First NLP & ML-Based Autoresponder
- The world's first NLP & ML-based autoresponder revolutionizes digital marketing
- Automates campaigns, saves resources, and allows scalability without a large marketing team
- Ensures emails reach the inbox, drives traffic, and boosts conversions
- Offers personalized multi-channel campaigns, voice, and video content for better engagement
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VentureBeat
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Calling all gen AI disruptors of the enterprise! Apply now to present at Transform 2025
- Transform 2025 is hosting the Innovation Showcase for generative AI products that can disrupt the enterprise.
- Selected presenters will have the opportunity to showcase their technology on the main stage in front of an invite-only audience.
- Winners will receive direct feedback, editorial coverage from VentureBeat, and recognition in three categories.
- Applications must be submitted by March 31, 2025, for a chance to present at the event.
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Medium
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How Genie-2, World Labs, and Amazon Nova Are Shaping the Future
- Genie-2 from Google DeepMind is an AI model that creates playable 3D environments from a single image prompt.
- World Labs has introduced depth-mapped worlds that generate realistic 3D environments based on depth maps.
- 11 Labs has launched conversational AI tools for natural voice interactions in 32 languages.
- Prime Intellect's decentralized training models democratize AI development by distributing computational tasks.
- Google's Gen Chess and Runway's Frames showcase AI's creativity in generative art and design.
- Amazon Nova is a series of multimodal AI models, offering scalability and cost efficiency.
- Amazon is developing Nova Premiere, a multimodal model designed for complex reasoning tasks.
- These advancements blur the line between human creativity and machine intelligence, shaping the future of AI.
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Medium
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279
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Top Open-Source Alternatives to The Productivity Apps
- Todo.txt is a customizable to-do list manager that uses plain text files for task management.
- Tasks.org is a fully open-source task management app with a user-friendly interface.
- Joplin is a powerful open-source note-taking and to-do application with markdown support and data sync across multiple platforms.
- Standard Notes is an open-source note-taking app with end-to-end encryption for enhanced security.
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Medium
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Day 16: Building Blocks of Neural Networks: Perceptrons and Multi-Layer Networks
- A perceptron is a decision-making unit for computers that takes inputs, weighs them, and outputs either a 1 or 0.
- Perceptrons can only solve simple problems and are not effective in classifying complex images.
- Multi-layer networks are teams of perceptrons working together and can solve more complex problems.
- Multi-layer networks consist of multiple layers, with each layer passing data to the next layer until a final decision is made.
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Medium
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26
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What Ivy League Degrees Don’t Teach You About American Voters
- Kamala Harris wasn’t elected because of the information gap between those in the halls of DC and the American Public.
- Most American classrooms do not teach students how to find trustworthy and factual information to make informed decisions.
- Democratic campaigns and staffers spend so much time trying to convince voters of the “great things” that Democrats have done for them.
- However, most Americans have no idea how to find the information to make an informed decision.
- Democratic campaigns need to make it easier for voters to interact with and discover information about politicians.
- This article discusses Democrasee.io, an AI Copilot for Voters, which helps solve the information gap and make politics as easy as ordering a toaster from Amazon.
- Democrasee.io uses AI and Data Science to distill political information into bite-sized insights that fit busy lifestyles.
- The AI-powered chatbot allows voters to discover campaign finances, legislative records, votes, hearings, and the personal and institutional finances of their legislative representatives.
- Democrasee.io is in the early stages of solving the problem, but users have discovered new facts about their representatives within 1 minute of using the app.
- Overall, Democrasee.io aims to fill the crucial gap between voters and politicians by providing a personalized and intuitive solution to access political information.
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Datarobot
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Customer spotlight: Personify Health’s thoughtful approach to AI adoption
- Personify Health is using AI-powered platform to empower millions of members across 190+ countries to manage their health.
- The company is accelerating AI adoption with more than 15 predictive and generative AI projects currently underway.
- To train models on constantly changing data across hundreds of models multiplied by millions of members, the company uses DataRobot's end-to-end platform.
- DataRobot allows the team to train multiple models simultaneously and compare outputs for the greatest possible accuracy.
- Personify Health has the best and brightest data scientists, engineers, and analysts on their team.
- The platform unifies AI analytics across teams, technologies, and data sources, and speeds the time to production.
- Generative AI will become a greater part of how the company enables its organization.
- Personify Health empowers consumers with smarter recommendations that are held to the highest ethical and legal standards.
- DataRobot makes it easier to build and manage AI models for keeping their team focus on delivering better health and wellbeing recommendations to customers.
- Personify Health reduced AI model development time by 82%.
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