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Tutorials• Apr 2, 2026

Quantum Simulations with Python

Run Quantum Experiments with Qiskit-Aer The post Quantum Simulations with Python appeared first on Towards Data Science.

#Towards Data Science#Medium

News• Apr 2, 2026

How to Build Production Ready AgentScope Workflows with ReAct Agents, Custom Tools, Multi-Agent Debate, Structured Output and Concurrent Pipelines

In this tutorial, we build a complete AgentScope workflow from the ground up and run everything in Colab. We start by wiring OpenAI through AgentScope and validating a basic model call to understand how messages and responses are handled. From there, we define custom tool functions, register them in...

#MarkTechPost#AI#News

Research• Apr 2, 2026

How Emotion Shapes the Behavior of LLMs and Agents: A Mechanistic Study

arXiv:2604.00005v1 Announce Type: new Abstract: Emotion plays an important role in human cognition and performance. Motivated by this, we investigate whether analogous emotional signals can shape the behavior of large language models (LLMs) and agents. Existing emotion-aware studies mainly treat em...

#ArXiv#Machine Learning#Academic

Research• Apr 2, 2026

Perspective: Towards sustainable exploration of chemical spaces with machine learning

arXiv:2604.00069v1 Announce Type: new Abstract: Artificial intelligence is transforming molecular and materials science, but its growing computational and data demands raise critical sustainability challenges. In this Perspective, we examine resource considerations across the AI-driven discovery pi...

#ArXiv#Machine Learning#Academic

Research• Apr 2, 2026

Evolution Strategies for Deep RL pretraining

arXiv:2604.00066v1 Announce Type: new Abstract: Although Deep Reinforcement Learning has proven highly effective for complex decision-making problems, it demands significant computational resources and careful parameter adjustment in order to develop successful strategies. Evolution strategies offe...

#ArXiv#Machine Learning#Academic

News• Apr 2, 2026

M5B Daily Perspective (Technical Deep Dive): Navigating the Complexities of AI Engineering and Architecture

The field of artificial intelligence is rapidly evolving, with new breakthroughs and advancements being made on a daily basis. As AI continues to permeate various aspects of our lives, the technical architecture and engineering challenges that come with it are becoming increasingly complex. In this technical deep dive, we will delve into the intricacies of AI engineering and architecture, exploring the latest developments, trends, and innovations that are shaping the industry. Recently, Anthropic's accidental takedown of thousands of Github repositories has sparked a heated debate about the importance of open-source code and the need for transparency in AI development. The incident highlights the challenges that companies face in balancing the need to protect their intellectual property with the desire to foster collaboration and innovation within the AI community. As the demand for AI solutions continues to grow, companies must navigate these complexities and find ways to strike a balance between secrecy and openness. Meanwhile, Meta's plans to power its upcoming Hyperion AI data center with 10 new natural gas plants have raised concerns about the environmental impact of large-scale AI operations. The increasing energy requirements of AI systems pose significant challenges for companies seeking to reduce their carbon footprint while maintaining the performance and efficiency of their operations. As the industry continues to grow, it is essential to develop more sustainable and environmentally friendly solutions that can support the increasing demands of AI computing. The development of production-ready AI pipelines is another critical aspect of AI engineering, as demonstrated by the recent tutorial on building a Gemma 3 1B Instruct Generation AI pipeline using Hugging Face Transformers, Chat Templates, and Colab Inference. This tutorial highlights the importance of creating scalable and efficient AI workflows that can be easily deployed and integrated into existing systems. The use of cloud-based platforms and tools, such as Colab, is becoming increasingly popular, as they provide a flexible and cost-effective way to develop and deploy AI models. The concept of enactive floors and state-space reversibility is also gaining traction, particularly in the context of safe AGI development. The idea of creating AI systems that can learn from their environment and adapt to new situations is critical for developing more robust and reliable AI models. The inversion error, which refers to the tendency of AI systems to hallucinate or produce incorrect results, is a significant challenge that must be addressed in order to create more trustworthy and transparent AI systems. As we look to the future, it is clear that the field of AI is poised for significant growth and innovation. The latest machine learning trends, such as the increasing use of multimodal models and the development of more efficient training algorithms, are expected to have a profound impact on the industry. However, the rising costs of training large models and the need for more sustainable and environmentally friendly solutions are significant challenges that must be addressed. The development of new tools and platforms, such as Z.ai's GLM-5V-Turbo, is helping to drive innovation in the field of AI. This native multimodal vision coding model is optimized for open-claw and high-capacity agentic engineering workflows, providing a powerful tool for developers and researchers. Similarly, the LangChain Newsletter and ADeLe are providing valuable insights and resources for AI practitioners, helping to advance the state-of-the-art in AI research and development. The job market is also reflecting the growing demand for AI talent, with companies such as Dotmatics, Bounteous, and Ketone-IQ seeking skilled professionals to fill key roles. The need for experts in AI engineering, product management, and content creation is becoming increasingly important, as companies seek to develop and deploy AI solutions that can drive business value and innovation. The use of satellite imagery and other forms of geospatial data is also becoming increasingly important, particularly in the context of environmental monitoring and conservation. Google's partnership with the Brazilian government to create a satellite imagery map to help protect the country's forests is a notable example of the potential for AI and geospatial data to drive positive change. In conclusion, the field of AI is rapidly evolving, with new breakthroughs and advancements being made on a daily basis. The technical architecture and engineering challenges that come with AI development are significant, but they also present opportunities for innovation and growth. As we look to the future, it is essential to prioritize transparency, sustainability, and collaboration, while also driving innovation and advancement in the field of AI. By doing so, we can unlock the full potential of AI and create a brighter, more sustainable future for all.

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News• Apr 2, 2026

M5B Daily Recap: 2026-04-01

Daily AI Recap: Apr 01, 2026 Welcome to today's curated briefing of the most important AI developments. 🗞️ Top Stories - Anthropic took down thousands of Github repos trying to yank its leaked source code — a move the company says was an accidenthttps://techcrunch.com/2026/04/01/anthropic-took-down-thousands-of-github-repos-trying-to-yank-its-leaked-source-code-a-move-the-company-says-was-an-accident/: Anthropic executives said it was an accident and retracted the bulk of the takedown notices.... - Meta’s natural gas binge could power South Dakotahttps://techcrunch.com/2026/04/01/metas-natural-gas-binge-could-power-south-dakota/: Meta's upcoming Hyperion AI data center will be powered by 10 new natural gas plants.... - How to Build a Production-Ready Gemma 3 1B Instruct Generation AI Pipeline with Hugging Face Transformers, Chat Templates, and Colab Inferencehttps://www.marktechpost.com/2026/04/01/how-to-build-a-production-ready-gemma-3-1b-instruct-generation-ai-pipeline-with-hugging-face-transformers-chat-templates-and-colab-inference/: In this tutorial, we build and run a Colab workflow for Gemma 3 1B Instruct using Hugging Face Transformers and HF Token, in a practical, reproducible, and easy-to-follow step-by-step manner. We begin... - Holo3: Breaking the Computer Use Frontierhttps://huggingface.co/blog/Hcompany/holo3: ... - Cognichip wants AI to design the chips that power AI, and just raised $60M to tryhttps://techcrunch.com/2026/04/01/cognichip-wants-ai-to-design-the-chips-that-power-ai-and-just-raised-60m-to-try/: The firm says it can can reduce the cost of chip development by more than 75% and cut the timeline by more than half.... - The Inversion Error: Why Safe AGI Requires an Enactive Floor and State-Space Reversibilityhttps://towardsdatascience.com/the-inversion-error-why-safe-agi-requires-an-enactive-floor-and-state-space-reversibility/: A systems design diagnosis of hallucination, corrigibility, and the structural gap that scaling cannot close The post The Inversion Error: Why Safe AGI Requires an Enactive Floor and State-Space Rever... - 7 Machine Learning Trends to Watch in 2026https://machinelearningmastery.com/7-machine-learning-trends-to-watch-in-2026/: A couple of years ago, most machine learning systems sat quietly behind dashboards.... - AI Reality Check: The Real Cost of Training Large Models And Why It’s Risinghttps://aiquantumintelligence.com/ai-reality-check-the-real-cost-of-training-large-models-and-why-its-rising: Edition 6 of AI Reality Check provides a contrarian breakdown of the rising costs behind large-scale AI model training. This article exposes the real economics of compute, energy, data, and infrastruc... - Less than a month: StrictlyVC San Francisco brings leaders from TDK Ventures, Replit, and more togetherhttps://techcrunch.com/2026/04/01/join-the-first-strictlyvc-of-2026-in-sf-with-leaders-from-tdk-ventures-and-replits-co-founder/: StrictlyVC San Francisco brings leaders from TDK Ventures, Replit, and more together on April 30. Space is limited. Register here for your pass.... - We’re creating a new satellite imagery map to help protect Brazil’s forests.https://blog.google/products-and-platforms/products/earth/satellite-imagery-brazilian-deforestation/: Google partnered with the Brazilian government on a satellite imagery map to help protect the country’s forests.... - The latest AI news we announced in March 2026https://blog.google/innovation-and-ai/technology/ai/google-ai-updates-march-2026/: March 2026 AI Recap showing new updates... - 5 lessons we can learn from Sora: Hype vs realityhttps://www.aiacceleratorinstitute.com/5-lessons-we-can-learn-from-sora-hype-vs-reality/: After ChatGPT’s breakthrough, the race to define the next frontier of generative AI accelerated. One of the most talked-about innovations was OpenAI’s Sora, a text-to-video AI model that promised to t... - What Happens Now That AI is the First Analyst On Your Team?https://towardsdatascience.com/what-happens-now-that-ai-is-the-first-analyst-on-your-team/: How I am adapting in my career in the age of AI, automation, and when everything moving faster than expected. The post What Happens Now That AI is the First Analyst On Your Team? appeared first on Tow... - Falcon Perceptionhttps://huggingface.co/blog/tiiuae/falcon-perception: ... - Structural Pass Analysis in Football: Learning Pass Archetypes and Tactical Impact from Spatio-Temporal Tracking Datahttps://arxiv.org/abs/2603.28916: arXiv:2603.28916v1 Announce Type: new Abstract: The increasing availability of spatio-temporal tracking data has created new opportunities for analysing tactical behaviour in football. However, many ... - Preview tool helps makers visualize 3D-printed objectshttps://news.mit.edu/2026/preview-tool-helps-makers-visualize-3d-printed-objects-0401: By quickly generating aesthetically accurate previews of fabricated objects, the VisiPrint system could make prototyping faster and less wasteful.... - ChartDiff: A Large-Scale Benchmark for Comprehending Pairs of Chartshttps://arxiv.org/abs/2603.28902: arXiv:2603.28902v1 Announce Type: new Abstract: Charts are central to analytical reasoning, yet existing benchmarks for chart understanding focus almost exclusively on single-chart interpretation rat... - Multimodal Embeddings and RAG: A Practical Guidehttps://weaviate.io/blog/multimodal-guide: Multimodal embeddings allow AI systems to search and reason across text, images, audio, and video in their native formats. This blog covers the key intuitions behind how this all works and walks throu... 🛠️ Featured Tools - Mercor says it was hit by cyberattack tied to compromise of open-source LiteLLM projecthttps://techcrunch.com/2026/03/31/mercor-says-it-was-hit-by-cyberattack-tied-to-compromise-of-open-source-litellm-project/: The AI recruiting startup confirmed a security incident after an extortion hacking crew took credit for stealing data from the company's systems.... - OneComp: One-Line Revolution for Generative AI Model Compressionhttps://arxiv.org/abs/2603.28845: arXiv:2603.28845v1 Announce Type: new Abstract: Deploying foundation models is increasingly constrained by memory footprint, latency, and hardware co... - Beta-Scheduling: Momentum from Critical Damping as a Diagnostic and Correction Tool for Neural Network Traininghttps://arxiv.org/abs/2603.28921: arXiv:2603.28921v1 Announce Type: new Abstract: Standard neural network training uses constant momentum typically 0.9, a convention dating to 1964 ... - A Neural Tension Operator for Curve Subdivision across Constant Curvature Geometrieshttps://arxiv.org/abs/2603.28937: arXiv:2603.28937v1 Announce Type: new Abstract: Interpolatory subdivision schemes generate smooth curves from piecewise-linear control polygons by re... - Foundations of Polar Linear Algebrahttps://arxiv.org/abs/2603.28939: arXiv:2603.28939v1 Announce Type: new Abstract: This work revisits operator learning from a spectral perspective by introducing Polar Linear Algebra,... - Working Paper: Towards a Category-theoretic Comparative Framework for Artificial General Intelligencehttps://arxiv.org/abs/2603.28906: arXiv:2603.28906v1 Announce Type: new Abstract: AGI has become the Holly Grail of AI with the promise of level intelligence and the major Tech compan... - Towards Computational Social Dynamics of Semi-Autonomous AI Agentshttps://arxiv.org/abs/2603.28928: arXiv:2603.28928v1 Announce Type: new Abstract: We present the first comprehensive study of emergent social organization among AI agents in hierarchi... - Enhancing Policy Learning with World-Action Modelhttps://arxiv.org/abs/2603.28955: arXiv:2603.28955v1 Announce Type: new Abstract: This paper presents the World-Action Model WAM, an action-regularized world model that jointly reas... - Mimosa Framework: Toward Evolving Multi-Agent Systems for Scientific Researchhttps://arxiv.org/abs/2603.28986: arXiv:2603.28986v1 Announce Type: new Abstract: Current Autonomous Scientific Research ASR systems, despite leveraging large language models LLMs... - Liquid AI Released LFM2.5-350M: A Compact 350M Parameter Model Trained on 28T Tokens with Scaled Reinforcement Learninghttps://www.marktechpost.com/2026/03/31/liquid-ai-released-lfm2-5-350m-a-compact-350m-parameter-model-trained-on-28t-tokens-with-scaled-reinforcement-learning/: In the current landscape of generative AI, the ‘scaling laws’ have generally dictated that more parameters equal more intelligence. However, Liquid AI... - Google AI Releases Veo 3.1 Lite: Giving Developers Low Cost High Speed Video Generation via The Gemini APIhttps://www.marktechpost.com/2026/03/31/google-ai-releases-veo-3-1-lite-giving-developers-low-cost-high-speed-video-generation-via-the-gemini-api/: Google has announced the release of Veo 3.1 Lite, a new model tier within its generative video portfolio designed to address the primary bottleneck fo... - Hugging Face Releases TRL v1.0: A Unified Post-Training Stack for SFT, Reward Modeling, DPO, and GRPO Workflowshttps://www.marktechpost.com/2026/04/01/hugging-face-releases-trl-v1-0-a-unified-post-training-stack-for-sft-reward-modeling-dpo-and-grpo-workflows/: Hugging Face has officially released TRL Transformer Reinforcement Learning v1.0, marking a pivotal transition for the library from a research-orien... - Gradient Labs gives every bank customer an AI account managerhttps://openai.com/index/gradient-labs: Gradient Labs uses GPT-4.1 and GPT-5.4 mini and nano to power AI agents that automate banking support workflows with low latency and high reliability.... - Speculative Decoding: How LLMs Generate Text 3x Fasterhttps://www.analyticsvidhya.com/blog/2026/04/speculative-decoding/: You probably use Google on a daily basis, and nowadays, you might have noticed AI-powered search results that compile answers from multiple sources. B... - The gig workers who are training humanoid robots at homehttps://www.technologyreview.com/2026/04/01/1134863/humanoid-data-training-gig-economy-2026-breakthrough-technology/: When Zeus, a medical student living in a hilltop city in central Nigeria, returns to his studio apartment from a long day at the hospital, he turns on... - How Can A Model 10,000× Smaller Outsmart ChatGPT?https://towardsdatascience.com/how-can-a-model-10000x-smaller-outsmart-chatgpt-2/: Why thinking longer can matter more than being bigger The post How Can A Model 10,000× Smaller Outsmart ChatGPT? appeared first on Towards Data Scienc... - How AIRA2 breaks AI research bottleneckshttps://www.aiacceleratorinstitute.com/how-aira2-breaks-ai-research-bottlenecks/: While we've seen remarkable progress in AI for coding and mathematics, creating agents that can navigate the messy, open-ended nature of real research... - 7 Essential AI Website Builders: From Prompt to Productionhttps://www.kdnuggets.com/7-essential-ai-website-builders-from-prompt-to-production: I reviewed dozens of AI website builders and found 7 that are worth testing.... - Build Better AI Agents with Google Antigravity Skills and Workflowshttps://www.kdnuggets.com/build-better-ai-agents-with-google-antigravity-skills-and-workflows: How to configure Antigravity AI agent workflows to resiliently automate critical code generation tasks: all without the need for third-party tools.... - ADeLe: Predicting and explaining AI performance across taskshttps://www.microsoft.com/en-us/research/blog/adele-predicting-and-explaining-ai-performance-across-tasks/: AI benchmarks report how large language models LLMs perform on specific tasks but provide little insight into their underlying capabilities that dri... - March 2026: LangChain Newsletterhttps://blog.langchain.com/march-2026-langchain-newsletter/: It feels like spring has sprung here, and so has a new NVIDIA integration, ticket sales for Interrupt 2026, and announcing LangSmith Fleet formerly A... - Z.ai Launches GLM-5V-Turbo: A Native Multimodal Vision Coding Model Optimized for OpenClaw and High-Capacity Agentic Engineering Workflows Everywherehttps://www.marktechpost.com/2026/04/01/z-ai-launches-glm-5v-turbo-a-native-multimodal-vision-coding-model-optimized-for-openclaw-and-high-capacity-agentic-engineering-workflows-everywhere/: In the field of vision-language models VLMs, the ability to bridge the gap between visual perception and logical code execution has traditionally fa... 💼 New Opportunities - Filestage: Customer Success Team Lead German Speakinghttps://weworkremotely.com/remote-jobs/filestage-customer-success-team-lead-german-speaking - EDUopinions: Student Representativeshttps://weworkremotely.com/remote-jobs/eduopinions-student-representatives-17 - Ketone-IQ: Content Producerhttps://weworkremotely.com/remote-jobs/ketone-iq-content-producer - LawnStarter: Director of Conversion Rate Optimizationhttps://weworkremotely.com/remote-jobs/lawnstarter-director-of-conversion-rate-optimization - HB Travels: Travel Reservation Agent Remotehttps://weworkremotely.com/remote-jobs/hb-travels-travel-reservation-agent-remote - Dotmatics: Product Manager | GraphPad Prismhttps://weworkremotely.com/remote-jobs/dotmatics-product-manager-graphpad-prism - Bounteous: Principal Product Lead MarTech AIhttps://weworkremotely.com/remote-jobs/bounteous-principal-product-lead-martech-ai - Sales Operations Project Managerhttps://remoteOK.com/remote-jobs/remote-sales-operations-project-manager-xsolla-1130954 - Biology AI Training Experthttps://remoteOK.com/remote-jobs/remote-biology-ai-training-expert-anyone-ai-1130953 - Operations Project Managerhttps://remoteOK.com/remote-jobs/remote-operations-project-manager-xsolla-1130947

View Daily Recap

News• Apr 1, 2026

Anthropic took down thousands of Github repos trying to yank its leaked source code — a move the company says was an accident

Anthropic executives said it was an accident and retracted the bulk of the takedown notices.

#News#AI#TechCrunch

News• Apr 1, 2026

Meta’s natural gas binge could power South Dakota

Meta's upcoming Hyperion AI data center will be powered by 10 new natural gas plants.

#News#AI#TechCrunch

News• Apr 1, 2026

How to Build a Production-Ready Gemma 3 1B Instruct Generation AI Pipeline with Hugging Face Transformers, Chat Templates, and Colab Inference

In this tutorial, we build and run a Colab workflow for Gemma 3 1B Instruct using Hugging Face Transformers and HF Token, in a practical, reproducible, and easy-to-follow step-by-step manner. We begin by installing the required libraries, securely authenticating with our Hugging Face token, and load...

#MarkTechPost#AI#News

Engineering• Apr 1, 2026

Holo3: Breaking the Computer Use Frontier

#HuggingFace#OpenSource#Models

News• Apr 1, 2026

Cognichip wants AI to design the chips that power AI, and just raised $60M to try

The firm says it can can reduce the cost of chip development by more than 75% and cut the timeline by more than half.

#News#AI#TechCrunch

Tutorials• Apr 1, 2026

The Inversion Error: Why Safe AGI Requires an Enactive Floor and State-Space Reversibility

A systems design diagnosis of hallucination, corrigibility, and the structural gap that scaling cannot close The post The Inversion Error: Why Safe AGI Requires an Enactive Floor and State-Space Reversibility appeared first on Towards Data Science.

#Towards Data Science#Medium

Tutorials• Apr 1, 2026

7 Machine Learning Trends to Watch in 2026

A couple of years ago, most machine learning systems sat quietly behind dashboards.

#Machine Learning#AI

News• Apr 1, 2026

AI Reality Check: The Real Cost of Training Large Models (And Why It’s Rising)

Edition 6 of AI Reality Check provides a contrarian breakdown of the rising costs behind large-scale AI model training. This article exposes the real economics of compute, energy, data, and infrastructure—and why chasing scale without efficiency is becoming unsustainable.

#AI Quantum Intelligence#AI#News

News• Apr 1, 2026

Less than a month: StrictlyVC San Francisco brings leaders from TDK Ventures, Replit, and more together

StrictlyVC San Francisco brings leaders from TDK Ventures, Replit, and more together on April 30. Space is limited. Register here for your pass.

#News#AI#TechCrunch

News• Apr 1, 2026

We’re creating a new satellite imagery map to help protect Brazil’s forests.

Google partnered with the Brazilian government on a satellite imagery map to help protect the country’s forests.

#Google#AI

News• Apr 1, 2026

The latest AI news we announced in March 2026

March 2026 AI Recap showing new updates

#Google#AI

Research• Apr 1, 2026

5 lessons we can learn from Sora: Hype vs reality

After ChatGPT’s breakthrough, the race to define the next frontier of generative AI accelerated. One of the most talked-about innovations was OpenAI’s Sora, a text-to-video AI model that promised to transform digital content creation.

#AI Accelerator Institute#AI#Research

Tutorials• Apr 1, 2026

What Happens Now That AI is the First Analyst On Your Team?

How I am adapting in my career in the age of AI, automation, and when everything moving faster than expected. The post What Happens Now That AI is the First Analyst On Your Team? appeared first on Towards Data Science.

#Towards Data Science#Medium

Engineering• Apr 1, 2026

Falcon Perception

#HuggingFace#OpenSource#Models

Research• Apr 1, 2026

Structural Pass Analysis in Football: Learning Pass Archetypes and Tactical Impact from Spatio-Temporal Tracking Data

arXiv:2603.28916v1 Announce Type: new Abstract: The increasing availability of spatio-temporal tracking data has created new opportunities for analysing tactical behaviour in football. However, many existing approaches evaluate passes primarily through outcome-based metrics such as scoring probabil...

#ArXiv#Machine Learning#Academic

Research• Apr 1, 2026

ChartDiff: A Large-Scale Benchmark for Comprehending Pairs of Charts

arXiv:2603.28902v1 Announce Type: new Abstract: Charts are central to analytical reasoning, yet existing benchmarks for chart understanding focus almost exclusively on single-chart interpretation rather than comparative reasoning across multiple charts. To address this gap, we introduce ChartDiff, ...

#ArXiv#Machine Learning#Academic

News• Apr 1, 2026

Preview tool helps makers visualize 3D-printed objects

By quickly generating aesthetically accurate previews of fabricated objects, the VisiPrint system could make prototyping faster and less wasteful.

#MIT#AI

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