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The past, present and future of chatbots

Chatbots have been around for decades, with the earliest version, ELIZA, released in 1967 as a simple rules-based program.
Jabberwocky in the 1980s enabled voice interaction, while A.L.I.C.E. in the 1990s allowed responses to prompt to inform future responses.
The shift from rules-based chatbots to data-driven models was driven by advancements in compute power and availability of data.
The development of large language models like ChatGPT, using GPT-3 architecture, enabled more varied and conversational responses.
Open-source machine learning libraries like PyTorch and TensorFlow have made developing chatbots more accessible for businesses.
Cost remains a barrier for heavy-duty chatbot use cases, with the need to consider GPU usage and model parameters.
Multi-modal models are the future of chatbots, allowing interactions through text, speech, imagery, video, and audio, enhancing creative capabilities.
Retrieval augmented generation (RAG) architectures empower chatbots to draw on proprietary data for advanced enterprise use cases.
As chatbots evolve with technologies like RAG systems and AI agents, the innovation potential for organizations is vast, promising efficiency gains.
In the future, multi-modal models and evolving technologies will continue to enhance the capabilities and efficiency of chatbots in various industries.

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Netflixtechblog

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FM-Intent: Predicting User Session Intent with Hierarchical Multi-Task Learning

FM-Intent is a novel recommendation model introduced by Netflix to predict user intents and enhance next-item recommendations through hierarchical multi-task learning.
The model aims to enrich the understanding of user sessions by incorporating the prediction of underlying user intents, offering a more nuanced recommendation experience.
FM-Intent utilizes implicit signals from user interaction metadata to predict various user intents related to actions, genre preferences, movie/show types, and time-since-release.
The model architecture of FM-Intent involves three main components: input feature sequence formation, user intent prediction using a Transformer encoder, and next-item prediction with hierarchical multi-task learning.
Experimental validation shows that FM-Intent outperforms state-of-the-art models, including Netflix's foundation model, in next-item prediction accuracy.
FM-Intent generates meaningful user intent embeddings for clustering users with similar intents, providing valuable insights into user viewing patterns and preferences.
The model has been integrated into Netflix's recommendation ecosystem, allowing for personalized UI optimization, enhanced recommendation signals, and search optimization based on user intent predictions.
By understanding user intents beyond next-item prediction, FM-Intent enhances Netflix's recommendation capabilities, delivering more personalized and relevant content recommendations.
The model's hierarchical multi-task learning approach and comprehensive experimental results demonstrate its effectiveness in improving recommendation accuracy and user experience.
FM-Intent signifies a significant advancement in Netflix's recommendation system, emphasizing the importance of user intent prediction for providing satisfying and tailored recommendations.

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Engadget

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Microsoft blames Apple for Xbox mobile store delays

Microsoft attributes the delay of the Xbox mobile app store to Apple's App Store rules, which prevent users from buying Microsoft mobile games through the Xbox web store on iOS.
In an amicus brief supporting Epic Games in their battle against Apple, Microsoft expresses concerns about Apple potentially overturning the injunction allowing payments outside of apps that bypass Apple's 30 percent fee.
Apple has filed an appeal against the injunction and requested the Ninth Circuit to halt enforcement of the ruling, while Microsoft is pushing for enforcement of the injunction during the appeal.
Microsoft aims to launch its own online store for in-app items to work around Apple's restrictions, but Apple's actions could hinder this effort.

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Medium

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A Sound Investment: The Echo-nomics Transforming Battery Diagnostics

High scrap rates in new facilities have reached up to 90%, costing the industry millions and hindering scalability.
Sention Technologies offers a diagnostic solution to improve battery production, reduce waste, and provide actionable insights for design and manufacturing.
Their Cell Intelligence Platform utilizes advanced techniques like ultrasonic Time-of-Flight measurement to detect defects early, streamlining production.
Co-founded by battery experts, Sention Technologies' innovative approach aims to revolutionize battery manufacturing by enhancing efficiency and sustainability.

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Journey to 1000 models: Scaling Instagram’s recommendation system

Instagram has successfully scaled its recommendation system to include over 1000 ML models while maintaining quality and reliability.
The algorithm involves multiple layers of ranking funnels, constant experimentation, and a large number of models serving user traffic.
Challenges in scaling included infra maturity lagging behind, slow model launches, and lack of consistent model quality definitions.
Solutions implemented included a model registry, automated model launch flow, and defining model stability metrics for all models.
The model registry streamlined model importance and business function information, improving operational response efficiency.
Implementing criticality levels based on incident severity and automation tools for launch processes enhanced productivity and reliability.
Model stability metrics were introduced to measure prediction accuracy, addressing issues faster and leading to higher-quality recommendations.
Lessons learned included the importance of infra understanding, enabling rapid model iteration, and ensuring reliability considers model quality.
Building robust tools and processes has not only improved operations but also empowered colleagues to drive innovation and growth.
The focus on quality and collaboration has been instrumental in Instagram's successful journey of scaling its recommendation system.

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VentureBeat

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OpenAI updates its new Responses API rapidly with MCP support, GPT-4o native image gen, and more enterprise features

OpenAI has released significant updates to its Responses API, introducing support for remote Model Context Protocol servers, image generation tools, and more enterprise features.
The Responses API, launched in March 2025, allows developers to build agentic applications leveraging technologies from AI services like ChatGPT and OpenAI's own AI agents.
Popular applications built with the API include coding agents, market intelligence assistants, and educational platforms.
The API combines elements from Chat Completions and Assistants API, offering built-in tools for web and file search, computer use, and autonomous workflows.
One key addition is support for remote MCP servers, enabling developers to connect OpenAI's models to external tools and services for seamless interaction.
The update introduces a new image generation model, 'gpt-image-1,' offering real-time streaming previews and multi-turn refinement.
The Code Interpreter tool is now integrated into the API, improving model performance in data analysis, math, and logic-based tasks.
Enhancements in file search functionality include searches across multiple vector stores and attribute-based filtering for relevant content retrieval.
Enterprise features like background mode for asynchronous tasks, reasoning summaries, and encrypted reasoning items cater to specific business needs.
New capabilities are supported across OpenAI's GPT-4o series, including o3 and o4-mini models, improving response accuracy and efficiency.

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Sdtimes

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Anchore SBOM, Komodor integrates into IDPs, and Shopify’s new dev tools – SD Times Daily Digest

Anchore released Anchore SBOM, allowing centralized management and analysis of SBOMs from internal and third-party sources in specific formats.
Komodor integrated into IDPs to simplify Kubernetes operations by providing real-time service status, troubleshooting, monitoring, access control, and fleet management capabilities.
Shopify introduced a new developer platform merging Dev Dashboard and CLI, featuring AI-powered code generation and dev stores for app preview, along with declarative custom data definitions and Storefront MCP for building shopping assistants.

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CSS-Tricks

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SVG to CSS Shape Converter

Temani Afif has created an extensive collection of CSS shapes with tools to generate them dynamically.
He has transitioned to using the shape() function over the path() function for creating complex shapes.
With the shape() function, generated CSS shapes provide more concise and readable code compared to path() commands.
The converter transforms SVG path coordinates into shape() commands, aiding in understanding and utilizing shape() more effectively.

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Hackernoon

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Nexchain Crypto Presale is Now at Stage 13

Nexchain is currently at Stage 13 of its presale and has raised $2.4 million, attracting attention from intelligent investors due to its innovative approach in developing a next-generation Layer-1 blockchain with real-world functionality and user-centric governance.
Nexchain offers fast block finality, low transaction costs, and NEX token for fee payments and validator incentives, along with staking opportunities for users to actively engage in network consensus.
The cryptocurrency market is witnessing notable developments, including Chiliz-Naver Pay collaboration, Cake Wallet's secret transactions feature for Bitcoin users, and MakerDAO's governance asset update to the SKY token.
Nexchain's performance in its presale signifies a shift in investor focus towards assets with tangible applications, solid tokenomics, and promising development potential, positioning it as a promising investment in the growing crypto market.

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Tech Radar

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The price of AI? Adobe hikes Creative Cloud subscriptions for some with new Pro plan – here’s what you need to know

Adobe is increasing the price of its Creative Cloud All Apps plan to $770 a year, including new AI tools and credits.
The pricing changes include the All Apps plan costing $104.99 per month for monthly subscriptions and $99.99 per month for corporate per-seat plans.
Student and teacher pricing will increase from $34.99 to $39.99, and the plan's name is changing to Creative Cloud Pro.
Adobe is focusing on AI tools, offering features like Generative Fill and Firefly Boards with 4,000 monthly credits for premium AI video, audio, and image generation.

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Tech Radar

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‘I made a lot of mistakes with Google Glass’: Google’s Sergey Brin admits missteps but says Android XR has a bright future for one big reason

Sergey Brin admits to making mistakes with Google Glass during a discussion at Google I/O 2025.
Brin acknowledges flaws of Google Glass launch and emphasizes the importance of polishing products before demoing them.
Google Glass, initially a cultural phenomenon, faced criticism and meme 'Glassholes'.
Brin lacked knowledge of consumer electronics supply chains leading to Google Glass pricing issues.
Partners like Samsung, Gentle Monster, and Warby Parker are now assisting in building Android XR Glasses.
Brin highlights the role of AI in enhancing the capabilities of smart glasses like Android XR.
Gemini, Google's generative AI platform, is central to enhancing the functionality of Android XR Glasses.
DeepMind CEO suggests that a universal assistant could be the key app for smart glasses like Android XR.
AI advancements and improved design make Android XR Glasses a promising venture for Google.
Android XR Glasses represent Brin's renewed focus on smart glasses technology and AI integration.

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Javacodegeeks

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Micronaut CLI (mn) Features Overview

The Micronaut CLI (mn) simplifies the creation and management of Micronaut projects, offering commands for project scaffolding, testing, and runtime operations.
Micronaut is a JVM-based framework for high-performance microservices and cloud-native systems, emphasizing compile-time processing for efficiency.
Key Micronaut features include compile-time DI, fast startup, GraalVM compatibility, reactive support, built-in web server, and cloud-native readiness.
The Micronaut CLI streamlines project setup, code generation, local running, testing, and feature management for improved development workflows.
Installation on macOS can be done via SDKMAN or manual download, while Windows users can manually install Micronaut CLI for native execution.
The Micronaut CLI offers features like data support, security configurations, messaging integrations, tracing, cloud deployments, and testing frameworks.
Developers can filter features with terminal commands to focus on specific capabilities like security, AWS integrations, data repositories, and cloud deployments.
Micronaut CLI empowers developers to tailor their projects with necessary components efficiently, enhancing modularity and performance.
By exploring and selectively including features, developers benefit from fine-grained control over their application stack for cloud-native and serverless architectures.
The Micronaut CLI's feature-rich toolkit and filtering options enable developers to optimize their tech stack and streamline microservice development.
Sign up for the newsletter to access Java skill development resources and stay informed about the latest Micronaut updates.

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TechBullion

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How Software Development Kits (SDKs) Are Empowering More Businesses

Software development kits (SDKs) are revolutionizing businesses, enabling them to integrate new functionalities and improve processes and analytics.
SDKs are considered critical tools for scaling and innovation, providing significant productivity gains for companies.
The role of SDKs is expanding, particularly in major tech firms, with a growing presence in diverse industries like fintech, healthcare, and e-commerce.
SDKs offer automated abstraction, reducing the need for in-depth coding knowledge and providing necessary tools upfront.
Businesses benefit from SDKs by reducing development costs, shortening time-to-market, and making complex features accessible to non-technical professionals.
SDKs enhance cost-efficiency, improve interoperability between platforms, and enable personalization, allowing businesses to scale efficiently.
While SDKs face challenges like security risks and a learning curve, they hold the potential to merge with AI, offering advanced capabilities and increased business potential.
The future of SDKs may involve cross-platform compatibility, sustainability optimization, and a focus on privacy compliance with regulations like CCPA and GDPR.
Businesses using SDKs, from hospitals to startups, can leverage code effectively, bridging the gap between expensive in-house development and off-the-shelf solutions.

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Medium

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Books, Code, and Curiosity: My Path as an AI Explorer After First Year

Importance of combining academic learning with real-world practice in the field of Artificial Intelligence.
Advice to start building projects, learning AI fundamentals early, and creating a public record of growth for standing out in the future.
Experience of a conversation with a brother studying for a PhD in AI, emphasizing the impact of small actions today on future opportunities.
Encouragement for students to start building, learning, and taking small steps to explore opportunities in software development and AI.

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Medium

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Exploring libp2p with Golang

Libp2p is a modular system of protocols, specifications, and libraries that simplifies peer-to-peer communication.
It was developed by Protocol Labs to facilitate peer-to-peer applications, allowing nodes to act as clients and servers.
Libp2p simplifies connecting nodes, discovering peers, secure communication, multiplexing streams, and managing transport protocols.
Decentralization is important as it enables direct communication between nodes, resource sharing, and routing data without centralized servers.

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