April, 2025

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How to Avoid Ethical Red Flags in Your AI Projects

Flipboard

As a computer scientist who has been immersed in AI ethics for about a decade, Ive witnessed firsthand how the field has evolved. Today, a growing number of engineers find themselves developing AI solutions while navigating complex ethical considerations. Beyond technical expertise, responsible AI deployment requires a nuanced understanding of ethical implications.

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DolphinGemma: Google AI model understands dolphin chatter

AI News

Google has developed an AI model called DolphinGemma to decipher how dolphins communicate and one day facilitate interspecies communication. The intricate clicks, whistles, and pulses echoing through the underwater world of dolphins have long fascinated scientists. The dream has been to understand and decipher the patterns within their complex vocalisations.

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US Sanctions Backfire: Huawei’s AI Chips Accelerate China’s Self-Reliance

Unite.AI

Huawei Technologies is preparing to mass-ship a pair of advanced artificial intelligence chips the Ascend 910C and upcoming Ascend 920 marking a big moment in the global AI hardware arena. These new chips are poised to fill a void left by U.S. export restrictions that have curbed Chinas access to top-tier AI accelerators from U.S. firms like Nvidia.

AI 275
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Repurposing Protein Folding Models for Generation with Latent Diffusion

BAIR

The actual text for the post content appears below. Text will appear on the homepage, i.e., [link] but we only show part of theac posts on the homepage. The rest is accessed via clicking 'Continue'. This is enforced with the `more` excerpt separator. --> PLAID is a multimodal generative model that simultaneously generates protein 1D sequence and 3D structure, by learning the latent space of protein folding models.

Robotics 271
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Precision in Motion: Why Process Optimization Is the Future of Manufacturing

Speaker: Jason Chester, Director, Product Management

In today’s manufacturing landscape, staying competitive means moving beyond reactive quality checks and toward real-time, data-driven process control. But what does true manufacturing process optimization look like—and why is it more urgent now than ever? Join Jason Chester in this new, thought-provoking session on how modern manufacturers are rethinking quality operations from the ground up.

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Generative AI Data Scientist: A Booming New Job Role

Analytics Vidhya

Summary Introduction Generative AI (GenAI) has evolved from experimental research to enterprise-grade applications in record time. The rise of tools like ChatGPT, AI-powered copilots, and custom AI agents across industries, has led to the emergence of a bunch of new roles and teams in organizations. One such booming new career path is that of a […] The post Generative AI Data Scientist: A Booming New Job Role appeared first on Analytics Vidhya.

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What is AI thinking? Anthropic researchers are starting to figure it out

Flipboard

Why are AI chatbots so intelligentcapable of understanding complex ideas, crafting surprisingly good short stories, and intuitively grasping what users mean? The truth is, we dont fully know. Large language models think in ways that dont look very human. Their outputs are formed from billions of mathematical signals bouncing through layers of neural networks powered by computers of unprecedented power and speed, and most of that activity remains invisible or inscrutable to AI researchers.

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Apple AI stresses privacy with synthetic and anonymised data

AI News

Apple is taking a new approach to training its AI models one that avoids collecting or copying user content from iPhones or Macs. According to a recent blog post , the company plans to continue to rely on synthetic data (constructed data that is used to mimic user behaviour) and differential privacy to improve features like email summaries, without gaining access to personal emails or messages.

Big Data 273
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How Google’s Geospatial Reasoning Can Transform Crisis and Climate Response

Unite.AI

Googles latest advancements in geospatial artificial intelligence (AI) are transforming how we interact with spatial data. By integrating generative AI with specialized geospatial models, Google has developed a framework for asking complex geospatial questions to their large language model, Gemini. This innovation enables professionals in fields like emergency response, city planning, and climate science to access faster and more efficient insights into critical geospatial intelligence.

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How AWS Sales uses generative AI to streamline account planning

AWS Machine Learning Blog

Every year, AWS Sales personnel draft in-depth, forward looking strategy documents for established AWS customers. These documents help the AWS Sales team to align with our customer growth strategy and to collaborate with the entire sales team on long-term growth ideas for AWS customers. These documents are internally called account plans (APs). In 2024, this activity took an account manager (AM) up to 40 hours per customer.

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Smart Tools & Strong Teams: A People-First Approach to AI in Sales

Speaker: Matt Sunshine, CEO at The Center for Sales Strategy

AI isn’t replacing salespeople—it’s empowering them. The most forward-thinking sales organizations are using AI to enhance human performance rather than eliminate it. From coaching and messaging to prospecting and pipeline accountability, artificial intelligence is giving managers and SDRs the new tools they need to work smarter, sell better, and close more.

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Vibe Coding, Vibe Checking, and Vibe Blogging

O'Reilly Media

For the past decade and a half, I’ve been exploring the intersection of technology, education, and design as a professor of cognitive science and design at UC San Diego. Some of you might have read my recent piece for O’Reilly Radar where I detailed my journey adding AI chat capabilities to Python Tutor , the free visualization tool that’s helped millions of programming students understand how code executes.

Python 100
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Seeing the Unseeable: How AI Reveals Atomic-Level Dynamics in Nanoparticles

NYU Center for Data Science

Observing atomic-level dynamics has been an elusive goal in materials science, limited by physics that forces scientists to choose between seeing fine details or capturing dynamic changes. Now, a breakthrough AI technique developed by CDS Associate Professor of Mathematics and Data Science Carlos Fernandez-Granda and his collaborators has shattered this barrier, allowing unprecedented observations of atoms inmotion.

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Machine learning-based prediction of heating values in municipal solid waste

Flipboard

In this research, our objective was to utilize different machine learning techniques, such as XGBoost, Extra Trees, CatBoost, and Multiple Linear Regression (MLR), to model the heating values of municipal solid waste. The input parameters considered for the constructed models included the weight of the dry sample (kg) and the content of carbon (C), hydrogen (H), oxygen (O), nitrogen (N), sulfur (S), and ash in kg.

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AI streamlines budgeting, but human oversight essential

AI News

Research conducted by Vlerick Business School has discovered that in the area of AI financial planning, the technology consistently outperforms humans when allocating budgets with strategic guidelines in place. Businesses that use AI for budgeting processes experience substantial improvements in the accuracy and efficiency of budgeting plans compared to human decision-making.

Big Data 268
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AI-Enabled Robotics Software for Manufacturing Automation: Speeding Time-to-Value

Robots are a cornerstone of a smart factory, automating a wide range of manufacturing tasks that are monotonous, physically straining, or even hazardous. However, real-world robotics deployments have not lived up to the revolutionary potential the industrial sector had originally envisioned. Robot implementations are typically confined to specific applications, carry high costs, and are time-consuming.

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Is Robot Exploitation Universal or Culturally Dependent?

Unite.AI

People in Japan treat cooperative artificial agents with the same level of respect as they do humans, while Americans are significantly more likely to exploit AI for personal gain, according to a new study published in Scientific Reports by researchers from LMU Munich and Waseda University Tokyo. As self-driving vehicles and other AI autonomous robots become increasingly integrated into daily life, cultural attitudes toward artificial agents may determine how quickly and successfully these techn

Robotics 261
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AI Workforce: using AI and Drones to simplify infrastructure inspections

AWS Machine Learning Blog

Inspecting wind turbines, power lines, 5G towers, and pipelines is a tough job. Its often dangerous, time-consuming, and prone to human error. Thats why we at Amazon Web Services (AWS) are working on AI Workforcea system that uses drones and AI to make these inspections safer, faster, and more accurate. This post is the first in a three-part series exploring AI Workforce, the AWS AI-powered drone inspection system.

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We’re Finally Starting to Understand How AI Works

Artificial Corner

Image made with GPT 4o Ever since I started developing, learning, and working with AI, there’s always been a component we in the tech world refer to as a black box—an element that can be, to some extent, unpredictable. Chances are, many of us have spent time analyzing outputs, tweaking training data, and digging into attention patterns. Still, a large part of the AI's decision-making process has remained hidden.

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Dimensional Data Modeling in the Modern Era: A Timeless Blueprint for Data Architecture

ODSC - Open Data Science

In a world of ever-evolving data tools and technologies, some approaches stand the test of time. Thats the case Dustin DorseyPrincipal Data Architect at Onyx makes for dimensional data modeling , a practice born in the 1990s that continues to provide clarity, performance, and scalability in modern data architecture. With nearly two decades of experience helping major enterprises build robust data platforms, Dorsey walks us through the enduring value of dimensional modeling and why its more relev

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The AI Productivity Shift: Whats Working & Whats Next

85% of teams are using AI, but only 27% report clear productivity gains. Why? Because most are still stuck in surface-level adoption. In this expert panel, top voices in workplace strategy and remote innovation—Dr. Gleb Tsipursky, Phil Kirschner, Nadia Harris, and Eryn Peters—reveal how leading teams are cutting digital noise, training AI to fit their workflows, and building cultures that embrace change.

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Man Alarmed as His Cognitive Skills Decay After Outsourcing Them to AI

Flipboard

It's a fact of life that automation can make us lazier. Usually, the tradeoffs are worth it. But it feels more pernicious with AI Chatbots, which offer to basically automate thinking itself. Th at's what Sam Schechner, a tech reporter for The Wall Street Journal , began to wise up to after developing a nasty ChatGPT habit. "Artificial intelligence was eating my brain," he wrote in a recent essay for the newspaper.

Chatbots 179
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Google introduces AI reasoning control in Gemini 2.5 Flash

AI News

Google has introduced an AI reasoning control mechanism for its Gemini 2.5 Flash model that allows developers to limit how much processing power the system expends on problem-solving. Released on April 17, this “thinking budget” feature responds to a growing industry challenge: advanced AI models frequently overanalyse straightforward queries, consuming unnecessary computational resources and driving up operational and environmental costs.

Big Data 235
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Self-Healing Data Centers: How AI Is Transforming IT Operations

Unite.AI

“If you could give my operations team just 30 minutes back every day, that would be a win.” One CIO's modest request reflects the reality of today's IT operations teamsstuck in reactive firefighting mode, running on fumes. But these 3 a.m. alert storms and scramble-to-recover moments that define traditional IT operations are becoming obsolete.

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Forward vs. Backward Reasoning in AI: How Artificial Intelligence Solves Problems

Pickl AI

Summary: Forward and backward reasoning in AI are crucial for logical inference and problem-solving. Forward reasoning starts with premises to deduce conclusions, while backward reasoning begins with a goal to find supporting premises. Both methods improve AI decision-making by enhancing logical deduction and inference capabilities. Introduction Artificial Intelligence (AI) often seems like magic.

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Agentic AI Explained: Smarter Conversations, Better Experiences

AI has transformed how enterprises deliver customer service, enabling faster engagement, problem-solving, and cost savings. However, traditional AI Agents often rely on rigid conversation flows, risking customer trust when conversations stray from predefined paths. These limitations prevent businesses from fully realizing AI’s potential for cost-efficiency and productivity.

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Evaluate models or RAG systems using Amazon Bedrock Evaluations – Now generally available

AWS Machine Learning Blog

Organizations deploying generative AI applications need robust ways to evaluate their performance and reliability. When we launched LLM-as-a-judge (LLMaJ) and Retrieval Augmented Generation (RAG) evaluation capabilities in public preview at AWS re:Invent 2024 , customers used them to assess their foundation models (FMs) and generative AI applications, but asked for more flexibility beyond Amazon Bedrock models and knowledge bases.

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Robot Co-Workers and Agentic AI: How the Future Workplace is Taking Shape

ODSC - Open Data Science

Robot co-workers may be arriving in your office sooner than expected, according to AI leaders who spoke at the recent Phoenix Global Forum, according to AXIOS. The panel discussion, focused on workplace AI adoption, offered a compelling look at how companies are scaling AI to transform productivity and prepare for a future with autonomous agents. Major ROI for Companies Using AI Intelligently Kellie Romack, Chief Digital Information Officer at ServiceNow, shared how AI is already delivering meas

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3 quick, easy AI chatbot prompts that can help you do your job better

Flipboard

Fun fact: The saying work smarter, not harder is coming up on its 100th birthday. Coined in the 1930s by industrial engineer Allen Morgenstern, this simple, pithy directive is arguably more achievable today than ever before. Thanks to generative AI chatbots such as OpenAIs ChatGPT , Googles Gemini , and Anthropics Claude , its never been easier to quickly create text, images, code, and more.

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RAGEN: AI framework tackles LLM agent instability

AI News

Researchers have introduced RAGEN, an AI framework designed to counter LLM agent instability when handling complex situations. Training these AI agents presents significant hurdles, particularly when decisions span multiple steps and involve unpredictable feedback from the environment. While reinforcement learning (RL) has shown promise in static tasks like solving maths problems or generating code, its application to dynamic, multi-turn agent training has been less explored.

LLM 258
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From Curiosity to Competitive Edge: How Mid-Market CEOs Are Using AI to Scale Smarter

Speaker: Lee Andrews, Founder at LJA New Media & Tony Karrer, Founder and CTO at Aggregage

This session will walk you through how one CEO used generative AI, workflow automation, and sales personalization to transform an entire security company—then built the Zero to Strategy framework that other mid-market leaders are now using to unlock 3.5x ROI. As a business executive, you’ll learn how to assess AI opportunities in your business, drive adoption across teams, and overcome internal resource constraints—without hiring a single data scientist.

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How Scammers Use AI in Banking Fraud

Unite.AI

AI has empowered fraudsters to sidestep anti-spoofing checks and voice verification, allowing them to produce counterfeit identification and financial documents remarkably quickly. Their methods have become increasingly inventive as generative technology evolves. How can consumers protect themselves, and what can financial institutions do to help? 1.

AI 254
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Deep Learning vs. Neural Networks: A Detailed Comparison

Pickl AI

Summary: Deep Learning vs Neural Network is a common comparison in the field of artificial intelligence, as the two terms are often used interchangeably. However, they differ in complexity and application. Neural Networks are foundational structures, while Deep Learning involves complex, layered networks like CNNs and RNNs, enabling advanced AI capabilities such as image recognition and natural language processing.

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AI Model Discovers New Lung Cancer Subtype Associated with Poor Survival

NYU Center for Data Science

Tumor cells rarely exist in isolation. Instead, they live within complex microenvironments populated by diverse immune cells, blood vessels, and supporting structures. Understanding this heterogeneity is crucial for precision cancer treatment, but examining the multidimensional data from tumor samples has traditionally required laborious manual work by pathologists.