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Research• Jun 24, 2026

Synergizing Physically Constrained MCMC and Chemical-Informed Gaussian Processes for Reaction Network Discovery

arXiv:2606.23757v1 Announce Type: new Abstract: Extracting interpretable governing equations from sparse, noisy chemical time-series data remains difficult because discrete reaction topology and continuous kinetic parameters are tightly coupled. We present PC-MCMC-CIGP, a reproducible gray-box work...

#ArXiv#Machine Learning#Academic

Research• Jun 24, 2026

Low-power analogue neural networks with trainable nonlinear connections for continuous control

arXiv:2606.23742v1 Announce Type: new Abstract: Physical neural networks promise low-power machine learning by computing directly with analogue device physics, but most architectures force nonlinear device responses to act as scalar weights. Inspired by Kolmogorov-Arnold networks, we place trainabl...

#ArXiv#Machine Learning#Academic

Research• Jun 24, 2026

A Survey on Federated Causal Discovery and Inference

arXiv:2606.23741v1 Announce Type: new Abstract: Causal reasoning, which encompasses the discovery of causal structures and the inference of causal effects, is fundamental to data-driven decision making. In practice, data for reliable causal analysis are often distributed across institutions and can...

#ArXiv#Machine Learning#Academic

Research• Jun 24, 2026

Weight-Space Geometry of Offline Reasoning Training

arXiv:2606.23740v1 Announce Type: new Abstract: Offline reinforcement-learning losses (RFT, RIFT, DFT, Offline GRPO, DPO) are widely used to distill reasoning from large teachers into smaller students, and are typically compared on downstream accuracy alone. We ask whether they are mechanistically ...

#ArXiv#Machine Learning#Academic

News• Jun 24, 2026

M5B Daily Perspective (The AI Philosopher): The Echoes of Intelligence

As we delve into the realm of artificial intelligence, we find ourselves entwined in a complex dance of human ingenuity and technological advancements. The AI and Society Forum, recently held at MIT, serves as a poignant reminder of the critical questions that surround the integration of AI into our daily lives. Leading researchers gathered to examine the societal impacts of AI, sparking a conversation that echoes the very essence of human existence. It is in these moments that we are compelled to ponder the true meaning of intelligence, and whether the creations of our minds can truly replicate the intricacies of human thought. The pursuit of creating intelligent machines has led us down a path of discovery, where the lines between human and artificial intelligence begin to blur. The development of tools like NVIDIA Canary-1B-v2, designed for automatic speech recognition, translation, and subtitle export, demonstrates the remarkable capabilities of AI in processing and generating human language. Similarly, the emergence of platforms like Claude Code, which enables the creation of powerful loops, highlights the potential for AI to augment human creativity and problem-solving. Yet, as we continue to push the boundaries of what is possible, we must also consider the implications of our creations on the human experience. The marriage of human and artificial intelligence is a union that holds great promise, but also raises important questions about the future of work and the role of humans in an increasingly automated world. The recent layoffs in the tech industry, where AI has been cited as a factor, serve as a stark reminder of the challenges that lie ahead. As we navigate this uncharted territory, it is essential that we prioritize the development of skills that are uniquely human, such as empathy, creativity, and critical thinking. The article on the math skills required for data science serves as a timely reminder of the importance of foundational knowledge in navigating the complexities of AI. The story of immunologist Derya Unutmaz, who used GPT-5 to solve a three-year-old mystery, is a testament to the potential of AI to augment human capabilities. The ability of AI to process vast amounts of data, identify patterns, and provide insights that may elude human researchers is a powerful tool in the pursuit of knowledge. Similarly, the development of Anthropic's Claude Tag, which brings an AI teammate to Slack, demonstrates the potential for AI to enhance human collaboration and productivity. However, as we become increasingly reliant on these tools, we must also consider the potential risks and consequences of creating systems that are capable of learning and adapting at an unprecedented scale. The era of no-code AI, where individuals without extensive programming knowledge can create and deploy AI models, is a significant development that holds great promise for democratizing access to AI. However, it also raises important questions about the role of human judgment and oversight in the development and deployment of AI systems. The emergence of open web standards like WebMCP, which enables websites to expose structured tools directly to browsers, is a step towards creating a more transparent and accountable AI ecosystem. Furthermore, the development of tools like Mistral OCR 4, which provides citation-ready structured output, demonstrates the potential for AI to enhance human knowledge and understanding. As we continue to push the boundaries of what is possible with AI, it is essential that we prioritize the development of systems that are transparent, explainable, and aligned with human values. The release of Datalab's lift, a 9B open-weights vision model, serves as a reminder of the importance of creating systems that are capable of extracting structured information from complex data sources. The mental model for enterprise RAG, which views retrieval as filtering rather than search, is a valuable framework for understanding the complexities of AI-powered information retrieval. Ultimately, the creation of specialized AI systems that can be trusted is a critical challenge that requires a deep understanding of human values and the complexities of the human experience. In conclusion, the echoes of intelligence that surround us are a reminder of the complex and multifaceted nature of human existence. As we continue to create and deploy AI systems, we must prioritize the development of skills that are uniquely human, while also ensuring that our creations are aligned with human values and promote the well-being of all individuals. The future of AI is a future that is inherently human, and it is our responsibility to shape it in a way that reflects the best of human ingenuity and compassion. As we move forward, it is essential that we remain vigilant, curious, and committed to creating a world where human and artificial intelligence coexist in harmony, each augmenting and enriching the other in a beautiful dance of discovery and exploration.

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News• Jun 24, 2026

M5B Daily Recap: 2026-06-23

Daily AI Recap: Jun 23, 2026 Welcome to today's curated briefing of the most important AI developments. 🗞️ Top Stories - Exploring the societal impacts of AIhttps://news.mit.edu/2026/exploring-societal-impacts-of-ai-0623: During the AI and Society Forum, leading MIT researchers examined critical questions about AI’s influence on employment and democracy.... - How to Use NVIDIA Canary-1B-v2 for ASR, Translation, and Automatic SRT Subtitle Export in Pythonhttps://www.marktechpost.com/2026/06/23/how-to-use-nvidia-canary-1b-v2-for-asr-translation-and-automatic-srt-subtitle-export-in-python/: In this tutorial, we build a multilingual ASR and speech translation pipeline with NVIDIA Canary-1B-v2. We load the model on a GPU-enabled runtime, prepare audio into 16 kHz mono, and run English ASR.... - How to Create Powerful Loops in Claude Codehttps://towardsdatascience.com/how-to-create-powerful-loops-in-claude-code/: Learn about the concept of loops to power your coding agents. The post How to Create Powerful Loops in Claude Code appeared first on Towards Data Science.... - The Math Skills Every Aspiring Data Scientist Needs to Master Before Writing a Single Line of Codehttps://www.kdnuggets.com/20206/06/deasilex/the-math-skills-every-aspiring-data-scientist-needs-to-master-before-writing-a-single-line-of-code: This article breaks down each essential math discipline, explains its role in data science, and maps out an efficient learning path you can start today.... - How GPT-5 helped immunologist Derya Unutmaz solve a 3-year-old mysteryhttps://openai.com/index/gpt-5-immunology-mystery: GPT-5 Pro helped solve a 3-year-old immunology mystery, offering insights into T cell behavior. The breakthrough could support cancer and autoimmune research.... - Anthropic’s Claude Tag is learning your company, one Slack message at a timehttps://techcrunch.com/2026/06/23/anthropics-claude-tag-is-learning-your-company-one-slack-message-at-a-time/: Anthropic’s new Claude Tag brings an always-on AI teammate to Slack. But beyond productivity, the feature is a strategic play to capture organizational context, institutional knowledge, and enterprise... - I Spent an Hour on a Data Preprocessing Task Before Asking Geminihttps://towardsdatascience.com/i-spent-an-hour-on-a-data-preprocessing-task-before-asking-gemini/: How Gemini solved my Pandas problem in seconds, and why data science fundamentals still matter to spot suboptimal solutions The post I Spent an Hour on a Data Preprocessing Task Before Asking Gemini a... - Here’s Why WebMCP is Excitinghttps://www.kdnuggets.com/heres-why-webmcp-is-exciting: WebMCP is an open web standard that lets websites expose structured, callable tools directly to browser-based agents. Find out what makes it exciting.... - The Era of No-Code AI: What You Need to Knowhttps://towardsdatascience.com/the-era-of-no-code-ai-what-you-need-to-know/: If you are a programmer and you don't feel "special" anymore, you are not alone The post The Era of No-Code AI: What You Need to Know appeared first on Towards Data Science.... - NVIDIA Powers Over 400 of the World’s 500 Fastest Supercomputershttps://blogs.nvidia.com/blog/top500-green500-supercomputers-isc-2026/: News Highlights: NVIDIA technology runs 81% of the TOP500 and 90% of the systems new to the list. 26 systems on the TOP500 adopted the NVIDIA Grace CPU, up eight from the previous list. The top eight ... - GLM-5.2 OpenAI-Compatible API: A Hands-On Guide to Reasoning Effort, Function Calling, and Long-Context Retrievalhttps://www.marktechpost.com/2026/06/22/glm-5-2-openai-compatible-api-a-hands-on-guide-to-reasoning-effort-function-calling-and-long-context-retrieval/: We build a practical GLM-5.2 workflow using its hosted, OpenAI-compatible API instead of running the model locally. We set up multiple providers, load the API key securely, and create a reusable chat ... - On the Identifiability of User Adaptation in Co-Adaptive Neural Interfaceshttps://arxiv.org/abs/2606.20569: arXiv:2606.20569v1 Announce Type: new Abstract: We analyze identifiability in co-adaptive human-machine systems. We show that closed-loop encoder estimates do not uniquely identify user adaptation, b... - The running list: major tech layoffs in 2026 where employers cited AIhttps://techcrunch.com/2026/06/22/the-running-list-major-tech-layoffs-in-2026-where-employers-cited-ai/: A running look — in reverse chronological order — at the bigger tech companies that have announced significant layoffs this year with AI as a stated factor.... 🛠️ Featured Tools - OpenAI launches new initiative to help find and patch open-source bugshttps://techcrunch.com/2026/06/22/openai-launches-new-initiative-to-help-find-and-patch-open-source-bugs/: OpenAI is attempting to tackle the security issues of the open source software community.... - Toward More Controllable AI Video Editing: An Early Research Exploration at Netflixhttps://netflixtechblog.com/toward-more-controllable-ai-video-editing-an-early-research-exploration-at-netflix-eb8160ed60a2?source=rss----2615bd06b42e---4: By Zhuoning Yuan, Ta-Ying Cheng, Benjamin Klein, Bahareh AzarnoushIntroductionAt Netflix, we build technology to help storytellers bring their creativ... - New chip could help tiny robots traverse complex environmentshttps://news.mit.edu/2026/new-chip-could-help-tiny-robots-traverse-complex-environments-0623: Researchers combined an efficient algorithm with dedicated hardware to rapidly generate 3D maps for navigation using minimal memory and power.... - Beyond Fixed Budgets: Characterizing the Inelasticity and Limitations of Tree-of-Thought Reasoning Strategieshttps://arxiv.org/abs/2606.20599: arXiv:2606.20599v1 Announce Type: new Abstract: Tree of Thought ToT search has become a promising direction for improving the reasoning capabilitie... - The New Associationism: Lessons from Deep Learninghttps://arxiv.org/abs/2606.20600: arXiv:2606.20600v1 Announce Type: new Abstract: What can the success of modern AI tell us about how humans learn? This paper argues that taking AI se... - Specifying AI-SDLC Processes: A Protocol Language for Human-Agent Boundarieshttps://arxiv.org/abs/2606.20615: arXiv:2606.20615v1 Announce Type: new Abstract: AI agents now participate as first-class team members across the software development lifecycle, yet ... - PEAR: Permutation-Equivariant Adaptive Routing Multi-Agent Debatehttps://arxiv.org/abs/2606.20621: arXiv:2606.20621v1 Announce Type: new Abstract: Multi-agent debate improves the reliability of large language models LLMs through iterative peer cr... - NVIDIA Brings Trusted, 24/7 AI Agents to Telecom Operationshttps://blogs.nvidia.com/blog/telecom-ai-agents-dtw-ignite-2026/: Telecom operators have seen remarkable returns from using generative AI to automate network management, customer care and back-office operations. Most... - Prime Intellect Releases prime-rl 0.6.0 to Train Trillion-Parameter MoE Models on Agentic RL Workloadshttps://www.marktechpost.com/2026/06/23/prime-intellect-releases-prime-rl-0-6-0-to-train-trillion-parameter-moe-models-on-agentic-rl-workloads/: Prime Intellect has released prime-rl 0.6.0, an open framework for asynchronous reinforcement learning on trillion-parameter Mixture-of-Experts models... - How Omio is building the future of conversational travelhttps://openai.com/index/omio: Discover how Omio uses OpenAI to power conversational travel experiences, accelerate product development, and transform into an AI-native company.... - Shipping huggingfacehub every week with AI, open tools, and a human in the loophttps://huggingface.co/blog/huggingface-hub-release-ci: ... - The $400 million machine powering the future of chipmakinghttps://www.technologyreview.com/2026/06/23/1138837/asml-400-million-dollar-machine-powering-future-of-chipmaking/: Jos Benschop is climbing a ladder to get to the top of his newest machine. It’s a bit of a schlep. The contraption is the size of a double-decker bus... - Principal Drifthttps://www.oreilly.com/radar/principal-drift/: Over the past year I’ve reviewed enterprise agent architectures at roughly two dozen organizations, including banks, retailers, healthcare systems, an... - Build Your Own Local AI Coding Agent with Gemma 4 and OpenCodehttps://towardsdatascience.com/build-your-own-local-ai-coding-agent-with-gemma-4-and-opencode-2/: From installing Ollama to launching OpenCode with a local model, step by step. The post Build Your Own Local AI Coding Agent with Gemma 4 and OpenCode... - Clustering Unstructured Text with LLM Embeddings and HDBSCANhttps://machinelearningmastery.com/clustering-unstructured-text-with-llm-embeddings-and-hdbscan/: The current era of Generative AI seems to primarily focus on chat interfaces and prompts, but the range of applications of large language models , or ... - Sakana Fugu: Multi-Agent System as a Modelhttps://www.analyticsvidhya.com/blog/2026/06/sakana-fugu-multi-agent-system-as-a-model/: For years, AI progress has centered on scaling individual foundation models: larger parameters, longer context windows, stronger reasoning, and better... - Build real agentic apps using CUGA: two dozen working examples on a lightweight harnesshttps://huggingface.co/blog/ibm-research/cuga-apps: ... - 5 Essential Approaches to Robust Outlier Detectionhttps://www.kdnuggets.com/5-essential-approaches-to-robust-outlier-detection: Outliers can easily ruin the performance of any predictive analysis models you build: robustly detecting and handling them is crucial in any data proj... - Metric-Dependent Annotation Saturation for Learning from Label Distributionshttps://machinelearning.apple.com/research/metric-dependent-annotation-saturation: When annotators disagree on a label, the disagreement itself carries signal—and the number of annotators needed to capture it depends on the evaluatio... - How Businesses Are Building Specialized AI They Can Trusthttps://blogs.nvidia.com/blog/nvidia-agent-toolkit-open-models-tools-skills-secure-runtime-ai-agents/: Companies are asking how to build specialized AI that fits with the way their workflows actually run. The first wave of enterprise AI was about acces... - Retrieval Is Filtering, Not Search: A Mental Model for Enterprise RAGhttps://towardsdatascience.com/retrieval-is-filtering-not-search-a-mental-model-for-enterprise-rag/: Enterprise Document Intelligence Vol.1 7A - Stop searching strings. Filter linedf and tocdf. Pick anchors small, expand context large The post Re... - Experimenting with the proposed Cross-Origin Storage API in Transformers.jshttps://huggingface.co/blog/cross-origin-storage: ... - Nine Judges, Two Effective Votes: Correlated Errors Undermine LLM Evaluation Panelshttps://machinelearning.apple.com/research/correlated-llm-evaluation-panels: LLM-as-a-judge panels aggregate votes from multiple models, with the expectation that diverse models yield more reliable evaluations. We develop a fra... - Datalab Releases lift: A 9B Open-Weights Vision Model That Extracts Structured JSON From PDFs Using Schemashttps://www.marktechpost.com/2026/06/23/datalab-releases-lift-a-9b-open-weights-vision-model-that-extracts-structured-json-from-pdfs-using-schemas/: Datalab released lift, a 9B open-weights vision model that turns PDFs and images into schema-matching JSON. It uses schema-constrained decoding for va... - Helping build shared standards for advanced AIhttps://openai.com/index/helping-build-shared-standards-for-advanced-ai: OpenAI helps build shared standards for advanced AI, supporting evaluation frameworks, safety practices, and global cooperation through the Appia Foun... - Mistral OCR 4 Brings Citation-Ready Structured Output to RAG, Agentic, and Enterprise Search Pipelineshttps://www.marktechpost.com/2026/06/23/mistral-ocr-4/: Mistral AI released OCR 4 on June 23, 2026, moving from clean text extraction to structured document output. Each block returns a bounding box, a type... - India’s MoEngage bets that the future of marketing is millions of AI agentshttps://techcrunch.com/2026/06/23/indias-moengage-bets-marketings-future-on-millions-of-ai-agents/: The all-cash deal gives MoEngage access to technology that assigns AI agents to individual customers.... 🎁 Exclusive Offers - 4 days left to save up to $190 on TechCrunch Founder Summit 2026https://techcrunch.com/2026/06/23/4-days-left-to-save-up-to-190-on-techcrunch-founder-summit-2026/ 💼 New Opportunities - MapTiler: 🤝 Developer Relations & Customer Success Manager | Maps Platform Remote in Europehttps://weworkremotely.com/remote-jobs/maptiler-developer-relations-customer-success-manager-maps-platform-remote-in-europe - Fika Jobs raises $4M to build a video-first hiring platform where AI agents interview candidateshttps://techcrunch.com/2026/06/23/fika-jobs-raises-4m-to-build-a-video-first-hiring-platform-where-ai-agents-interview-candidates/ - Turtles: Customer Happiness Advocate Remote - Canadhttps://weworkremotely.com/remote-jobs/turtles-customer-happiness-advocate-remote-canad - The Podcast Consultant: The Podcast Consultant | Account Manager Full-Time Contracthttps://weworkremotely.com/remote-jobs/the-podcast-consultant-the-podcast-consultant-account-manager-full-time-contract - Golf Carts of ATX: Inbound/Outbound Sales - Remote - English language - No accent preferredhttps://weworkremotely.com/remote-jobs/golf-carts-of-atx-inbound-outbound-sales-remote-english-language-no-accent-preferred

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News• Jun 23, 2026

Exploring the societal impacts of AI

During the AI and Society Forum, leading MIT researchers examined critical questions about AI’s influence on employment and democracy.

#MIT#AI

News• Jun 23, 2026

How to Use NVIDIA Canary-1B-v2 for ASR, Translation, and Automatic SRT Subtitle Export in Python

In this tutorial, we build a multilingual ASR and speech translation pipeline with NVIDIA Canary-1B-v2. We load the model on a GPU-enabled runtime, prepare audio into 16 kHz mono, and run English ASR. We then translate speech into French, German, Spanish, and Italian, and extract word and segment ti...

#MarkTechPost#AI#News

Tutorials• Jun 23, 2026

How to Create Powerful Loops in Claude Code

Learn about the concept of loops to power your coding agents. The post How to Create Powerful Loops in Claude Code appeared first on Towards Data Science.

#Towards Data Science#Medium

Tutorials• Jun 23, 2026

The Math Skills Every Aspiring Data Scientist Needs to Master Before Writing a Single Line of Code

This article breaks down each essential math discipline, explains its role in data science, and maps out an efficient learning path you can start today.

#KDnuggets#Data Science#Learning

News• Jun 23, 2026

Anthropic’s Claude Tag is learning your company, one Slack message at a time

Anthropic’s new Claude Tag brings an always-on AI teammate to Slack. But beyond productivity, the feature is a strategic play to capture organizational context, institutional knowledge, and enterprise workflows.

#News#AI#TechCrunch

News• Jun 23, 2026

How GPT-5 helped immunologist Derya Unutmaz solve a 3-year-old mystery

GPT-5 Pro helped solve a 3-year-old immunology mystery, offering insights into T cell behavior. The breakthrough could support cancer and autoimmune research.

#GenAI#Textual#OpenAI

Tutorials• Jun 23, 2026

I Spent an Hour on a Data Preprocessing Task Before Asking Gemini

How Gemini solved my Pandas problem in seconds, and why data science fundamentals still matter to spot suboptimal solutions The post I Spent an Hour on a Data Preprocessing Task Before Asking Gemini appeared first on Towards Data Science.

#Towards Data Science#Medium

Tutorials• Jun 23, 2026

Here’s Why WebMCP is Exciting

WebMCP is an open web standard that lets websites expose structured, callable tools directly to browser-based agents. Find out what makes it exciting.

#KDnuggets#Data Science#Learning

Tutorials• Jun 23, 2026

The Era of No-Code AI: What You Need to Know

If you are a programmer and you don't feel "special" anymore, you are not alone The post The Era of No-Code AI: What You Need to Know appeared first on Towards Data Science.

#Towards Data Science#Medium

Hardware• Jun 23, 2026

NVIDIA Powers Over 400 of the World’s 500 Fastest Supercomputers

News Highlights: NVIDIA technology runs 81% of the TOP500 and 90% of the systems new to the list. 26 systems on the TOP500 adopted the NVIDIA Grace CPU, up eight from the previous list. The top eight systems on the Green500 run on NVIDIA GPUs and nine of the top 10 use NVIDIA technologies. No. […]

#NVIDIA#GPU#Enterprise

News• Jun 23, 2026

GLM-5.2 OpenAI-Compatible API: A Hands-On Guide to Reasoning Effort, Function Calling, and Long-Context Retrieval

We build a practical GLM-5.2 workflow using its hosted, OpenAI-compatible API instead of running the model locally. We set up multiple providers, load the API key securely, and create a reusable chat wrapper. We then test thinking-effort control, streamed reasoning, function calling, a tool-using ag...

#MarkTechPost#AI#News

Research• Jun 23, 2026

On the Identifiability of User Adaptation in Co-Adaptive Neural Interfaces

arXiv:2606.20569v1 Announce Type: new Abstract: We analyze identifiability in co-adaptive human-machine systems. We show that closed-loop encoder estimates do not uniquely identify user adaptation, but instead reflect properties of the joint system. We discuss implications for interpreting behavior...

#ArXiv#Machine Learning#Academic

News• Jun 23, 2026

The running list: major tech layoffs in 2026 where employers cited AI

A running look — in reverse chronological order — at the bigger tech companies that have announced significant layoffs this year with AI as a stated factor.

#News#AI#TechCrunch

News• Jun 23, 2026

M5B Daily Perspective (Industry Monographic): Navigating the AI Revolution in Key Sectors

The world of artificial intelligence is evolving at an unprecedented pace, with new developments and innovations emerging daily. As AI continues to permeate various industries, it is crucial to examine the impact of these advancements on specific sectors. In this editorial analysis, we will delve into the recent news and trends in the AI landscape, focusing on the disruptions and transformations occurring in key industries. The data center industry, for instance, is undergoing a significant shift with the introduction of new cooling systems. Nvidia's recent announcement of a cutting-edge cooling system that reduces water usage within data centers is a notable development. While this innovation is a step in the right direction, it is essential to acknowledge that it only addresses a fraction of the broader water consumption issue associated with AI. The production and training of AI models require substantial amounts of energy and water, which can have devastating environmental consequences. As the demand for AI continues to grow, it is imperative for industry leaders to prioritize sustainability and develop comprehensive solutions to mitigate the environmental impact of AI. In the realm of virtual assistants, Amazon is expanding its reach in India by testing Alexa+ with Hindi support. This move demonstrates the company's commitment to catering to diverse linguistic needs and increasing its market share in the region. The integration of Hindi support will enable Amazon to tap into the vast and growing Indian market, where language barriers have historically hindered the adoption of virtual assistants. As AI-powered virtual assistants become more prevalent, companies must adapt to the unique requirements of various markets and languages to remain competitive. The development of AI workspaces is another area that has seen significant advancements. ChatLLM by Abacus AI, for example, offers a multi-model AI workspace designed for daily work. This platform supports various AI models, agents, and coding tools, providing users with a comprehensive suite of features to streamline their workflow. The ability to encode categorical data for outlier detection is a critical aspect of AI model development, and alternative encodings are being explored to improve the efficiency and accuracy of these models. As AI workspaces continue to evolve, it is essential to focus on creating intuitive and user-friendly interfaces that cater to the needs of diverse users. The scaling of AI models is a complex and costly process, with hidden expenses that can catch companies off guard. A recent live session with practitioners from Barndoor AI highlighted the importance of anticipating and planning for these costs. The encoding of categorical data, for instance, can be a time-consuming and resource-intensive process, especially when dealing with large datasets. To get ahead of these costs, companies must invest in robust infrastructure, develop efficient encoding strategies, and prioritize model optimization. Moreover, the use of coding agents, such as Claude Code, can help verify work and streamline the development process. In the field of document intelligence, the ability to clarify vague questions and learn from default responses is crucial. The RAG Retrieve, Augment, Generate framework, for example, enables users to ask focused clarification questions and learn from default responses. This capability is particularly useful in enterprise settings, where the ability to extract relevant information from large documents can be a significant competitive advantage. As AI-powered document intelligence continues to advance, companies must focus on developing intuitive interfaces that can handle complex queries and provide accurate responses. The recent deployment of PP-OCRv6 on Hugging Face, a 50-language OCR Optical Character Recognition system, demonstrates the rapid progress being made in the field of natural language processing. This system, which can handle a vast range of languages, from 1.5M to 34.5M parameters, has significant implications for industries such as finance, healthcare, and education. The ability to accurately recognize and extract text from images and documents can revolutionize the way companies process and analyze data, leading to increased efficiency and productivity. The emergence of exascale supercomputers, such as JUPITER, is another significant development in the AI landscape. These powerful machines, which can perform complex calculations at unprecedented speeds, are poised to revolutionize fields such as scientific research, climate modeling, and materials science. The NAIRR Science Program, powered by NVIDIA AI infrastructure, is a notable example of how exascale computing can be leveraged to drive scientific breakthroughs. As exascale computing becomes more widespread, companies must invest in developing AI models and applications that can harness the full potential of these powerful machines. The design of interactive dashboards is another area that has seen significant advancements, with the development of Prefab reactive UI components and static HTML export. These tools enable developers to create interactive dashboards entirely in Python, providing a high degree of customization and flexibility. The use of Codex, a coding agent, can also help preserve context and manage complex projects, ensuring that work continues uninterrupted. As AI-powered dashboards become more prevalent, companies must focus on creating intuitive and user-friendly interfaces that provide real-time insights and actionable recommendations. In conclusion, the AI revolution is transforming industries at an unprecedented pace, with new developments and innovations emerging daily. As companies navigate this complex landscape, it is essential to prioritize sustainability, develop comprehensive solutions to mitigate the environmental impact of AI, and invest in robust infrastructure to support the scaling of AI models. By focusing on these key areas and staying ahead of the curve, companies can unlock the full potential of AI and drive significant growth and innovation in their respective industries.

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News• Jun 23, 2026

M5B Daily Recap: 2026-06-22

Daily AI Recap: Jun 22, 2026 Welcome to today's curated briefing of the most important AI developments. 🗞️ Top Stories - Nvidia wants to cut data center water use, but that’s not the same as fixing AI’s water problemhttps://techcrunch.com/2026/06/22/nvidia-wants-to-cut-data-center-water-use-but-thats-not-the-same-as-fixing-ais-water-problem/: Nvidia announced a new cooling system that cuts water use inside the data center. But it does nothing to address AI's biggest water use — fossil fuel power plants.... - Amazon is testing Alexa+ in India with Hindi supporthttps://techcrunch.com/2026/06/22/amazon-is-testing-alexa-in-india-with-hindi-support/: Amazon sent emails to customers inviting them to test Alexa+... - ChatLLM by Abacus AI Review: A Multi-Model AI Workspace Built for Daily Workhttps://www.kdnuggets.com/2026/06/abacus/abacus-ai-chatllm-review: An in-depth review of ChatLLM by Abacus AI, covering supported AI models, AI agents, coding tools, integrations, pricing, usage limits, and how it compares to ChatGPT.... - Encoding Categorical Data for Outlier Detectionhttps://towardsdatascience.com/encoding-categorical-data-for-outlier-detection/: Why one-hot encoding isn’t always the best approach, and alternative encodings The post Encoding Categorical Data for Outlier Detection appeared first on Towards Data Science.... - The hidden costs of scaling AI and how to get ahead of themhttps://www.aiacceleratorinstitute.com/the-hidden-costs-of-scaling-ai/: A live session with practitioners from Barndoor AI... - How to Use Claude Code in Your Browserhttps://towardsdatascience.com/how-to-use-claude-code-in-your-browser/: Learn how to apply coding agents to verify work in your browser. The post How to Use Claude Code in Your Browser appeared first on Towards Data Science.... - When RAG Users Ask Vague Questions: Clarify Once, Learn the Defaulthttps://towardsdatascience.com/when-rag-users-ask-vague-questions-clarify-once-learn-the-default/: Enterprise Document Intelligence Vol.1 6bis - Ask one focused clarification, learn the default from the answer, stay silent next time The post When RAG Users Ask Vague Questions: Clarify Once, Lear... - PP-OCRv6 on Hugging Face: 50-Language OCR from 1.5M to 34.5M Parametershttps://huggingface.co/blog/PaddlePaddle/pp-ocrv6: ... - At ISC, JUPITER Shows What Exascale Science Looks Likehttps://blogs.nvidia.com/blog/jupiter-exascale-supercomputing-science/: JUPITER, Europe’s first exascale supercomputer at Germany’s Forschungszentrum Jülich, runs on NVIDIA Grace Hopper Superchips and NVIDIA Quantum-X800 InfiniBand networking — and it’s had a busy year. A... - NAIRR Science Program Reshapes Scientific Research, Powered by NVIDIA AI Infrastructurehttps://blogs.nvidia.com/blog/nairr-scientific-research-ai-infrastructure/: For the past two years, the U.S. National Science Foundation’s National Artificial Intelligence Research Resource NAIRR pilot program has driven innovative research across the U.S. for over 700 proj... - How to Design Python-First Interactive Dashboards with Prefab Reactive UI Components and Static HTML Exporthttps://www.marktechpost.com/2026/06/21/how-to-design-python-first-interactive-dashboards-with-prefab-reactive-ui-components-and-static-html-export/: In this tutorial, we build a Prefab application that creates interactive dashboards entirely in Python. We design an operations dashboard with reactive state, charts, tables, filters, forms, tabs, and... - Codex-maxxing for long-running workhttps://openai.com/index/codex-maxxing-long-running-work: Learn how Jason Liu uses Codex to preserve context, manage complex projects, and help work continue beyond a single prompt.... 🛠️ Featured Tools - Hotter Than a Hot Tub: The 45°C Breakthrough to Cool AI’s Biggest Machineshttps://blogs.nvidia.com/blog/liquid-cooling-ai-factories/: Hot tubs sit at about 38 to 40 degrees Celsius, warm enough that most people can only soak for about 15 minutes. NVIDIA’s newest AI servers can run th... - MoonMath AI Open-Sources a HIP Attention Kernel for AMD MI300X That Beats AITER v3 on Every Shape and Rounding Modehttps://www.marktechpost.com/2026/06/22/moonmath-ai-open-sources-a-hip-attention-kernel-for-amd-mi300x-that-beats-aiter-v3-on-every-shape-and-rounding-mode/: The HIP kernel uses one-instruction asm wrappers and an eight-wave pipeline to outperform AMD's AITER v3 on MI300X. The post MoonMath AI Open-Sources ... - Loop Engineeringhttps://www.oreilly.com/radar/loop-engineering/: The following article originally appeared on Addy Osmani’s blog and is being reposted here with the author’s permission. Loop engineering is replacing... - Claude’s Hidden Art Skill: Making Illustrations With Codehttps://www.analyticsvidhya.com/blog/2026/06/claude-image-generation/: Everyone says Claude can’t make pictures. That’s partly true. Here is the kind of art it makes on its own, with no plugins and no connectors: Drawn by... - Neural Networks, Explained for Beginners: Start Here If They’ve Confused Youhttps://towardsdatascience.com/neural-networks-explained-for-beginners-start-here-if-theyve-confused-you/: The intuition behind neural networks and why they need activation functions. The post Neural Networks, Explained for Beginners: Start Here If They’ve ... - 3 NLTK Tricks for Advanced Text Preprocessing & Linguistic Analysishttps://www.kdnuggets.com/3-nltk-tricks-for-advanced-text-preprocessing-linguistic-analysis: In this article, we will walk through three essential NLTK tricks to elevate your text preprocessing: preserving phrase integrity with the MWETokenize... - Building Browser-Using AI Agents in Pythonhttps://machinelearningmastery.com/building-browser-using-ai-agents-in-python/: Most AI agent tutorials start with an API.... - NVIDIA Vera CPU Opens the Way for Agentic Scientific AI at Los Alamos National Laboratoryhttps://blogs.nvidia.com/blog/nvidia-vera-cpu-los-alamos-national-laboratory/: Mission, Vision and Veritas — new Los Alamos National Laboratory LANL supercomputers to be built with HPE and NVIDIA — are tapping NVIDIA Vera CPUs ... - From Materials Simulation to Experimental Astronomy, New NVIDIA AI Software Unlocks Scientific Discoverieshttps://blogs.nvidia.com/blog/ai-for-science-software-cuda/: At the ISC conference running in Hamburg this week, NVIDIA is introducing new software that speeds AI for science, from chemistry and materials discov... - Eco Wave Power Turns Waves Into Watts With NVIDIA AI Infrastructure and Digital Twinshttps://blogs.nvidia.com/blog/eco-wave-power-ai-digital-twins/: The next era of AI will not be defined by compute alone. Its growth will be determined by energy. As accelerated computing scales across AI factories... - The founder conference built for growth: TechCrunch Founder Summit pass rates increase June 26https://techcrunch.com/2026/06/22/the-founder-conference-built-for-growth-techcrunch-founder-summit-pass-rates-increase-june-26/: Save up to $190 on your pass to TechCrunch Founder Summit 2026 by June 26, 11:59 p.m. PT. Designed for founders first on November 4 in Boston. Registe... - Here’s What Everyone Gets Wrong About Agentic AIhttps://www.kdnuggets.com/heres-what-everyone-gets-wrong-about-agentic-ai: Agentic AI is not failing because the technology is bad. It is failing because of five specific misconceptions that teams carry into their first deplo... - Patch the Planet: a Daybreak initiative to support open source maintainershttps://openai.com/index/patch-the-planet: OpenAI introduces Patch the Planet, a Daybreak initiative helping open-source maintainers find, validate, and fix vulnerabilities with AI and expert r... - Daybreak: Tools for securing every organization in the worldhttps://openai.com/index/daybreak-securing-the-world: OpenAI introduces new Daybreak tools, including Codex Security and GPT-5.5-Cyber, to help organizations find, validate, and patch vulnerabilities at s... - AI Weekly Issue 506: Washington Blocked One AI Lab. China Blacklisted 56 Companies.https://aiweekly.co/issues/washington-blocked-one-ai-lab-china-blacklisted-56-companies: Ten days after Washington pulled Anthropic's top models from foreign hands, the bill came due. This week Beijing blacklisted 56 American firms, Anthro... - Three things to watch amid Anthropic’s latest feud with the governmenthttps://www.technologyreview.com/2026/06/22/1139424/three-things-to-watch-amid-anthropics-latest-feud-with-the-government/: This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. For those of... - Google DeepMind bets $75M on AI’s future in Hollywood with A24 dealhttps://techcrunch.com/2026/06/22/google-deepmind-bets-75m-on-ais-future-in-hollywood-with-a24-deal/: Google DeepMind and A24 are teaming up to build AI filmmaking tools.... - Sakana AI Launches Sakana Fugu: An Orchestration Model That Routes Tasks Across a Swappable Pool of Frontier LLMshttps://www.marktechpost.com/2026/06/22/sakana-ai-launches-sakana-fugu-an-orchestration-model-that-routes-tasks-across-a-swappable-pool-of-frontier-llms/: Fugu and Fugu Ultra route tasks across a swappable model pool, leading most coding, reasoning, and agentic benchmarks. The post Sakana AI Launches Sak... - AI chipmaker Groq confirms $650M raise, re-staffs after Nvidia’s $20B not-acqui-hire dealhttps://techcrunch.com/2026/06/22/ai-chipmaker-groq-confirms-650m-raise-re-staffs-after-nvidias-20b-not-acqui-hire-deal/: What does an AI company do after one of those not-acqui-hire deals? Groq raised money, is leaning into its neocloud business, and hiring new execs.... - xAI Launches /goal in Grok Build, Adding Long-Running Autonomous Execution With Built-In Verification for Multi-Step Coding Taskshttps://www.marktechpost.com/2026/06/22/xai-launches-goal-in-grok-build-adding-long-running-autonomous-execution-with-built-in-verification-for-multi-step-coding-tasks/: xAI introduced /goal in Grok Build, a mode for long-running, autonomous task execution. You hand off one objective, and the agent plans an approach, e... - The AI world is getting ‘loopy’https://techcrunch.com/2026/06/22/the-ai-world-is-getting-loopy/: The loop takes agentic AI a step further, by authorizing a swarm of agents to work continuously in the background, endlessly.... - How Netflix Simplified Batch Compute with Kueuehttps://medium.com/netflix-techblog/how-netflix-simplified-batch-compute-with-kueue-87860682629c?source=rss----2615bd06b42e---4: By Alvin Bao, Alex Petrov, Jennifer Lai, Aidan Sherr, and Samartha ChandrashekarAs a part of the journey to transition Netflix’s compute infrastructur... 🎁 Exclusive Offers - SpaceX inks compute deal with Reflection AI, an open-source AI labhttps://techcrunch.com/2026/06/22/spacex-inks-compute-deal-with-reflection-ai-an-open-source-ai-lab/ - Google DeepMind bets $75M on AI’s future in Hollywood with A24 dealhttps://techcrunch.com/2026/06/22/google-deepmind-bets-75m-on-ais-future-in-hollywood-with-a24-deal/ - AI chipmaker Groq confirms $650M raise, re-staffs after Nvidia’s $20B not-acqui-hire dealhttps://techcrunch.com/2026/06/22/ai-chipmaker-groq-confirms-650m-raise-re-staffs-after-nvidias-20b-not-acqui-hire-deal/ 💼 New Opportunities - Collaborative Solutions: Workday Financials Analyst Consultant Global Delivery Centerhttps://weworkremotely.com/remote-jobs/collaborative-solutions-workday-financials-analyst-consultant-global-delivery-center - FIS Capital Markets: Account Manager IIhttps://weworkremotely.com/remote-jobs/fis-capital-markets-account-manager-ii - Snap Finance: Manager, Credit Card Business Strategy Remotehttps://weworkremotely.com/remote-jobs/snap-finance-manager-credit-card-business-strategy-remote - EY Studio+ Nederland: Oracle Services - Oracle Cloud Finance - Manager - Tech Cons - Open Locationhttps://weworkremotely.com/remote-jobs/ey-studio-nederland-oracle-services-oracle-cloud-finance-manager-tech-cons - Harris Global Business Services: Financial Accountanthttps://weworkremotely.com/remote-jobs/harris-global-business-services-financial-accountant

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News• Jun 22, 2026

Nvidia wants to cut data center water use, but that’s not the same as fixing AI’s water problem

Nvidia announced a new cooling system that cuts water use inside the data center. But it does nothing to address AI's biggest water use — fossil fuel power plants.

#News#AI#TechCrunch

News• Jun 22, 2026

Amazon is testing Alexa+ in India with Hindi support

Amazon sent emails to customers inviting them to test Alexa+

#News#AI#TechCrunch

Tutorials• Jun 22, 2026

ChatLLM by Abacus AI Review: A Multi-Model AI Workspace Built for Daily Work

An in-depth review of ChatLLM by Abacus AI, covering supported AI models, AI agents, coding tools, integrations, pricing, usage limits, and how it compares to ChatGPT.

#KDnuggets#Data Science#Learning

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