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VentureBeat

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Anthropic just made every Claude user a no-code app developer

  • Anthropic turns Claude into app platform, enabling users to create shareable applications easily.
  • Claude's intelligence embedded in creations allows for real-time adaptation and independent functionality.
  • Move signals shift to dynamic, interactive AI experiences, competing with OpenAI's Canvas feature.
  • Users can create smart tutors, data analyzers, and games without coding; moderation safeguards in place.

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Analyticsindiamag

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India’s Satellite Internet Scramble Has a Spectrum Problem

  • India's satellite internet ambitions face spectrum allocation challenges amid regulatory disagreements.
  • Players like Eutelsat OneWeb, Starlink, and Jio Satellite Communications Limited are gearing up.
  • Debate heats up over pricing, infrastructure parity, spectrum allotment policy, and fair competition.

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Analyticsindiamag

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LTTS Bags Another $50 Million Deal In Sustainability Segment

  • L&T Technology Services Limited (LTTS) secured a $50 million deal with a top energy company for its sustainability segment as a global engineering partner for Enterprise Data and Digital Services.
  • The partnership is an extension of a longstanding relationship between the two companies spanning over a decade.
  • LTTS will offer Enterprise Data and Digital Services to the client's affiliates worldwide as part of the agreement.
  • With extensive experience in engineering, digital services, and enterprise data management, LTTS aims to provide valuable insights to energy firms globally using its global delivery model.
  • The deal, structured as a long-term framework agreement, entrusts LTTS with greater responsibility for delivering top-quality digital services.
  • Amit Chadha, CEO of LTTS, highlighted the company's commitment to supporting the client's digital transformation and operational excellence through a combination of engineering expertise and advanced technologies.
  • In a recent development, LTTS also secured an $80 million contract with a US-based industrial products manufacturer for digital transformation purposes within the Sustainability segment.
  • This new deal win will lead LTTS to establish a Centre of Excellence in India to drive innovation for the client's digital transformation and product lifecycle management.

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Analyticsindiamag

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Murati’s Startup Bets on ‘RL for Business’ After Raising $2 Bn

  • Former OpenAI CTO Mira Murati's startup, Thinking Machines Lab, has raised $2 billion from investment firm Andreessen Horowitz at a $10 billion valuation.
  • TML focuses on creating custom AI solutions for businesses to boost revenue, described as 'RL for businesses'.
  • The startup plans to provide industry-specific AI solutions for customer support, retail, and investment banking, potentially with premium pricing.
  • TML is also developing a consumer-facing product like a chatbot and collaborates with Google Cloud for powerful NVIDIA servers, attracting interest from other cloud providers.

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Analyticsindiamag

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Coralogix introduces Olly, an advanced AI-Powered Observability Agent in India

  • Coralogix has launched Olly, an AI-Powered Observability Agent aimed at enhancing enterprise observability.
  • Olly allows users at all management levels to access observable data and receive real-time insights.
  • Ariel Assaraf, CEO of Coralogix, emphasizes Olly as an intelligent assistant empowering data-driven decision-making.
  • The launch in India is part of Coralogix's global expansion drive following a successful $115 million Series E funding round.
  • India's observability market is projected to reach $280.3 million by 2030, with a growing demand for scalable observability solutions.
  • Olly addresses challenges like managing data volume and quality, leveraging AI to provide contextual insights.
  • Observability has gained strategic importance post major outages, emphasizing the need for robust solutions like Olly.
  • Platforms like Olly offer real-time feedback, predictive alerts, and deep system visibility, crucial for preventing incidents like the CrowdStrike outage in 2024.
  • By embedding intelligence, Olly positions Coralogix at the forefront of AI-native infrastructure.
  • Observability is seen as crucial for operational continuity and future autonomous operations.
  • Olly combines advanced AI with telemetry data to support smarter decision-making.
  • The launch of Olly in India aligns with the increasing demand for observability solutions in the market.
  • Coralogix's valuation has surpassed $1 billion, driven by customer growth and demand for observability solutions.
  • The launch of Olly comes amidst rising demand for advanced observability solutions in the face of persistent industry challenges.
  • Olly's intelligence aims to help enterprises overcome data management issues and AI expertise shortages.
  • The introduction of Olly positions Coralogix as a significant player in the observability and AI-powered infrastructure landscape.

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Analyticsindiamag

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Foxconn to Invest $1.49 Billion to Set Up iPhone Manufacturing Facility in India

  • Foxconn, also known as Hon Hai, has received approval for investments totaling over $2.2 billion in the US and India.
  • The investment in India includes $1.49 billion to set up a new facility for manufacturing smartphone components.
  • Foxconn is diversifying its production beyond China, with India seen as a key destination for iPhone manufacturing.
  • Nearly 97 percent of iPhones assembled in India between March and May this year were exported to the US.
  • India's role in iPhone manufacturing is growing, with exports estimated at $3.2 billion.
  • Foxconn is proceeding with investments in India despite pressure to bring production back to the US.
  • Experts predict that India-made iPhones could make up 30 percent of global shipments by 2025.
  • Hon Hai is expanding its production footprint globally, with plants and offices in various countries.
  • The investments reflect Foxconn's efforts to reduce dependency on single markets and de-risk its supply chain.

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Dev

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Oreo's Top K Treats (Bucket Sort)

  • Oreo, a data-driven Persian cat with a treat addiction, sets out to determine the top treats in its daily feast using bucket sort.
  • Oreo encounters the 'Top K Frequent Elements' problem and uses bucket sort for a quick solution.
  • By analyzing recent treat data provided by its human, Oreo identifies shrimp and cookies as the top treats.
  • Oreo first counts treat frequencies using a Map and then organizes treats into frequency-based buckets.
  • The bucket sort approach allows Oreo to efficiently find its top K treats while avoiding traditional sorting complexities.
  • The time complexity of the approach is O(n), making it a linear time solution well-suited for this specific problem.
  • The space complexity is also O(n) due to the use of a map for storing treat counts and buckets for frequency organization.
  • Oreo's top 2 treats, shrimp and cookies, are confirmed to appear 3 times each based on the bucket sort results.

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Medium

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No Verifier? No Problem: Reinforcement Learning with Reference Probabilities

  • RLPR (Reinforcement Learning with Reference Probability Reward) is proposed to address the limitation of RLVR in general domains without verifiers.
  • RLVR is often restricted to math and code tasks due to the reliance on domain-specific verifiers for rewards.
  • RLPR uses the model's own probability of generating a reference answer as a reward signal, eliminating the need for external verifiers.
  • This self-rewarding setup alleviates manual reward engineering and enhances scalability across different domains.
  • The authors present two main technical contributions in the RLPR framework.
  • Experiments conducted on 7 benchmarks and 3 model families (Qwen, Llama, Gemma) demonstrate that RLPR improves general reasoning and outperforms verifier-free baselines and even specialized verifier methods like LLMs.
  • The code for RLPR has been made publicly available.

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Analyticsindiamag

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Google Accidentally Leaks Its Open-Source Gemini CLI Ahead of Launch

  • Google has accidentally leaked Gemini CLI, an open-source command-line interface designed to bring Gemini AI models to developers' terminals.
  • Gemini CLI is expected to offer high-capacity usage for free with full integration with Google's Gemini Code Assist.
  • The tool is released under the Apache 2.0 license to support coding, content creation, research, and task automation.
  • It allows up to 1,000 free requests daily and provides a one-million-token context window for users.
  • Gemini CLI boasts the industry's largest usage allowance at 60 model requests per minute with 1,000 model requests per day at no charge.
  • The interface supports extensibility via the Model Context Protocol (MCP) and supports AI invocation within scripts.
  • Prompt grounding with Google Search and structured system prompts via GEMINI.md are also included in Gemini CLI.
  • This release aligns Gemini CLI with Gemini Code Assist, facilitating seamless transitions between terminal and IDE workflows.
  • Gemini Code Assist is a free AI coding tool supporting all programming languages with features like code completion, generation, chat, and natural language prompts.
  • The Gemini CLI appeared unexpectedly following Google's emphasis on open agentic frameworks and high-trust developer tools.
  • There has been no official correction or clarification from Google regarding this accidental leak.

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Analyticsindiamag

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Anthropic Proves in Court Using Copyright Content for AI Training is Fair

  • A federal judge in San Francisco ruled that Anthropic's use of copyrighted books to train its AI system is fair use under US copyright law.
  • Judge William Alsup found Anthropic's AI training transformative as it analyzed writing, extracted uncopyrightable data, and developed new technology.
  • Training the large language model (LLM) was considered transformative as it aimed to teach statistical relationships between words to generate new text.
  • The process was compared to learning how to write by reading books rather than copying them verbatim.
  • There was no evidence that Anthropic's model reproduced or directly substituted the original works.
  • Anthropic downloaded millions of copyrighted books from various sources, including pirate sites, to train its AI model.
  • The court ruled that obtaining books through piracy infringed authors' copyrights and was not protected as fair use.
  • A trial is scheduled in December to determine damages related to the infringement.
  • The case originated from a class action lawsuit by authors alleging Anthropic used unauthorized copies of their books for training its AI model.
  • While training AI on lawfully obtained works is legal, relying on pirated materials was criticized for undermining copyright protections.
  • The ruling is considered significant for the AI industry, affirming fair use with legally obtained materials but cautioning against piracy.
  • Various companies, including OpenAI, Meta, and Stability AI, are facing legal challenges over alleged unauthorized use of copyrighted material for training AI models.
  • The decision is anticipated to impact copyright disputes in the AI industry, with appeals and further litigation likely to follow.

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Medium

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Brownian Motion: The Art of Getting Lost on a Chessboard

  • Brownian motion is a random walk where each step is unpredictable, resulting in a jagged trail on a chessboard.
  • Speeding up the process creates Brownian motion, where tiny steps lead to a continuous, irregular path.
  • Brownian motion is essential because randomness is prevalent in various aspects of life like weather, stock markets, and molecular movements.
  • It is a mathematical model for uncertainty, describing chaos and finding structure in unpredictable situations.

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Analyticsindiamag

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Anthropic’s Claude to Support Memory and App Creation: Reports

  • Anthropic is introducing two major updates to its AI assistant Claude: a memory function and expanded app creation tools.
  • The memory feature will allow Claude to recall past user interactions, bringing it closer to competitors' persistent memory functions.
  • The update is expected to launch on web and mobile platforms, but an official release date is pending confirmation.
  • Claude's Artifacts feature is evolving into an app canvas where users can embed Claude's functionality.
  • This update could enable users to create interactive, Claude-powered utilities without coding.
  • Anthropic aims to transform Claude into a no-code development platform for AI-driven mini-apps.
  • An advanced version of Artifacts is anticipated to be released soon, focusing on empowering users to build applications with Claude.
  • These updates may reduce technical barriers for creating custom AI solutions, setting Claude apart in the AI assistant landscape.

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Analyticsindiamag

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Animal Health Firm Zoetis Partners with Infosys to Integrate Advanced AI Solutions

  • Infosys and Zoetis have entered a strategic collaboration to enhance Zoetis’ IT operations and digital capabilities using advanced AI solutions.
  • The partnership aims to provide greater agility for Zoetis to adapt to changing business landscapes and customer needs.
  • The collaboration will help Zoetis deliver value to veterinarians, livestock producers, and pet owners globally by improving operational efficiency.
  • Zoetis plans to lead the animal health industry by leveraging digital innovation through this collaboration.
  • Infosys aims to reduce operational complexity for Zoetis and support their long-term business objectives through this partnership.
  • Zoetis expanded its global capability center in Hyderabad last year to drive technological innovation in its portfolio.
  • The expansion in Hyderabad is expected to create high-end technology roles focused on AI, machine learning, data science, ERP, and more.
  • Zoetis emphasizes the importance of technology, data, and analytics in the rapidly evolving animal healthcare industry.
  • The company is seeking talent with expertise in technologies like SAP S4 HANA, Salesforce, and others to meet future needs.

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Medium

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Leading Alone: How To Manage When No One’s Coming To Help

  • Transitioning from an engineer to a manager means needing to make decisions independently.
  • The challenge lies in handling issues without immediate guidance or support.
  • A scenario is outlined where an engineering manager faces resistance in addressing technical debt.
  • Dealing with resource constraints can lead to a cycle of problems that are hard to fix at the root.
  • Managers often face challenges dealing with technical debt and people issues due to competing priorities.
  • Strategies are discussed for building resilience as a manager in the face of challenges.
  • Tips include using technology to review meetings for insights and seeking external perspectives.
  • Adopting methods like rubber duck debugging and talking out problems can aid in decision-making.
  • Writing down thoughts after tough conversations can help clarify one's perspective.
  • Being resourceful in seeking solutions, including leveraging online resources and communities, is vital for managers.
  • Developing self-reassurance and confident decision-making skills are keys to successful management in a potentially solitary role.

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Analyticsindiamag

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Microsoft Launches Mu, a Small Language Model That Runs Locally on Copilot+ PCs

  • Microsoft has introduced Mu, a compact on-device language model designed to run on Copilot+ PCs' neural processing units.
  • Mu is built on a Transformer encoder-decoder architecture for efficient inference by separating input and output tokens, achieving over 100 tokens per second.
  • The 330 million parameter model was trained using Azure's A100 GPUs and incorporates features like dual LayerNorm and rotary positional embeddings for speed and accuracy.
  • Microsoft applied post-training quantisation, collaborating with hardware partners like AMD, Intel, and Qualcomm to optimize the model for lower-precision formats on edge devices.
  • Mu, integrated into Windows Settings, facilitates system adjustments via natural language queries, mapping them to system actions for user convenience.
  • The model performed best on multi-word queries with clear intent, implying the need for sufficient context for accurate interpretation.
  • Taskspecific fine-tuning enabled Mu to meet performance and latency goals, scaling the training dataset and support for various system settings.
  • Mu's development builds on prior models Phi and Phi Silica, expected to underpin future AI agents on Windows devices.

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