Wed.Oct 02, 2024

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How MNOs Are Leveraging AI to Revolutionize the Telecom Industry

Unite.AI

For more than three decades, mobile network operators (MNOs) have been channeling their research and development efforts into five key areas: messaging, roaming, policy, signaling, and clearing. Given the vast quantities of data processed through these systems, it's only natural that MNOs are increasingly focusing on leveraging artificial intelligence (AI) to enhance features, maximize resource efficiency, and safeguard customer data, all while fulfilling their service commitments.

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Automating Email Sorting and Labelling with CrewAI

Analytics Vidhya

Introduction Never would have the inventor of email –Ray Tomlinson– thought of how far this piece of tech would reach in the future. Today, email is the prime pillar of corporate and professional communications and is used in innumerable facets of the working world. And this has propelled the creation of a whole set of […] The post Automating Email Sorting and Labelling with CrewAI appeared first on Analytics Vidhya.

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How Microsoft’s TorchGeo Streamlines Geospatial Data for Machine Learning Experts

Unite.AI

In today’s data-driven world, geospatial information is essential for gaining insights into climate change, urban growth, disaster management, and global security. Despite its vast potential, working with geospatial data presents significant challenges due to its size, complexity, and lack of standardization. Machine learning can analyze these datasets yet preparing them for analysis can be time-consuming and cumbersome.

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How IBM Data Product Hub helps you unlock business intelligence potential

IBM Journey to AI blog

Business intelligence (BI) users often struggle to access the high-quality, relevant data necessary to inform strategic decision making. These professionals encounter a range of issues when attempting to source the data they need, including: Data accessibility issues: The inability to locate and access specific data due to its location in siloed systems or the need for multiple permissions, resulting in bottlenecks and delays.

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Usage-Based Monetization Musts: A Roadmap for Sustainable Revenue Growth

Speaker: David Warren and Kevin O’Neill Stoll

Transitioning to a usage-based business model offers powerful growth opportunities but comes with unique challenges. How do you validate strategies, reduce risks, and ensure alignment with customer value? Join us for a deep dive into designing effective pilots that test the waters and drive success in usage-based revenue. Discover how to develop a pilot that captures real customer feedback, aligns internal teams with usage metrics, and rethinks sales incentives to prioritize lasting customer eng

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10 Best Employee Engagement Software Platforms (October 2024)

Unite.AI

Many of today's employee engagement platforms are leveraging artificial intelligence to improve how organizations connect with, develop, and retain their workforce. These AI-powered solutions are transforming traditional HR processes, offering unprecedented insights into employee sentiment, streamlining onboarding procedures, and personalizing learning and development initiatives.

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Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

AWS Machine Learning Blog

Large enterprises are building strategies to harness the power of generative AI across their organizations. However, scaling up generative AI and making adoption easier for different lines of businesses (LOBs) comes with challenges around making sure data privacy and security, legal, compliance, and operational complexities are governed on an organizational level.

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Logic-of-Thought: Enhancing Logical Reasoning in Large Language Models through Propositional Logic Augmentation

Marktechpost

Large Language Models (LLMs) have made significant strides in various Natural Language Processing tasks, yet they still struggle with mathematics and complex logical reasoning. Chain-of-Thought (CoT) prompting has emerged as a promising approach to enhance reasoning capabilities by incorporating intermediate steps. However, LLMs often exhibit unfaithful reasoning, where conclusions don’t align with the generated reasoning chain.

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Elevate workforce productivity through seamless personalization in Amazon Q Business

AWS Machine Learning Blog

Personalization can improve the user experience of shopping, entertainment, and news sites by using our past behavior to recommend the products and content that best match our interests. You can also apply personalization to conversational interactions with an AI-powered assistant. For example, an AI assistant for employee onboarding could use what it knows about an employee’s work location, department, or job title to provide information that is more relevant to the employee.

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Researchers from KAIST and Google AI Introduce Blockwise Parallel Decoding (BCD): An AI Method for Rescoring Algorithms for Improved Efficiency and Fluency in Language Models

Marktechpost

Recent advances in autoregressive language models have brought about an amazing transformation in the field of Natural Language Processing (NLP). These models, such as GPT and others, have exhibited excellent performance in text creation tasks, including question-answering and summarization. However, their high inference latency poses a significant barrier to their general application, particularly in highly deep models with hundreds of billions of parameters.

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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Generating Coding Tests for LLMs: A Focus on Spark SQL

databricks

Introduction Applying Large Language Models (LLMs) for code generation is becoming increasingly prevalent, as it helps you code faster and smarter. A primary.

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Top 10 ChatGPT Use Cases for Businesses

Marktechpost

ChatGPT is a versatile tool with immense potential for businesses across diverse industries. Its capability to comprehend and generate human-like text enables its use in numerous applications, making it valuable for companies aiming to optimize operations, boost customer engagement, and foster innovation. Let’s look at the top 10 ChatGPT use cases for businesses, showcasing how it can be effectively leveraged to meet various needs.

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How to embed AI/BI Dashboards into your websites and applications

databricks

We are thrilled to announce that embedding for AI/BI Dashboards is now available. Embedding enables you to seamlessly integrate Databricks AI/BI Dashboards into.

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Prithvi WxC Released by IBM and NASA: A 2.3 Billion Parameter Foundation Model for Weather and Climate

Marktechpost

Climate and weather prediction has experienced rapid advancements through machine learning and deep learning models. Researchers have started to rely on artificial intelligence (AI) to enhance predictions’ accuracy and computational efficiency. Traditional numerical weather prediction (NWP) models have been effective but require substantial computational resources, making them less accessible and harder to apply at larger scales.

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From Diagnosis to Delivery: How AI is Revolutionizing the Patient Experience

Speaker: Simran Kaur, Founder & CEO at Tattva Health Inc.

The healthcare landscape is being revolutionized by AI and cutting-edge digital technologies, reshaping how patients receive care and interact with providers. In this webinar led by Simran Kaur, we will explore how AI-driven solutions are enhancing patient communication, improving care quality, and empowering preventive and predictive medicine. You'll also learn how AI is streamlining healthcare processes, helping providers offer more efficient, personalized care and enabling faster, data-driven

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Brave New World: Leo AI and Ollama Bring RTX-Accelerated Local LLMs to Brave Browser Users

NVIDIA

Editor’s note: This post is part of the AI Decoded series , which demystifies AI by making the technology more accessible, and showcases new hardware, software, tools and accelerations for GeForce RTX PC and NVIDIA RTX workstation users. From games and content creation apps to software development and productivity tools, AI is increasingly being integrated into applications to enhance user experiences and boost efficiency.

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Instructive Decoding (ID): A Novel AI Method that Enhances the Attention of Instruction-Tuned LLMs Towards Provided Instructions during the Generation Phase without Any Parameter Updates

Marktechpost

Instruction-tuned LMs have shown remarkable zero-shot generalization but often fail on tasks outside their training data. These LMs, built on large datasets and billions of parameters, excel in In-Context Learning (ICL), generating responses based on a few examples without re-training. However, the training dataset’s scope limits its effectiveness on unfamiliar tasks.

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Nintendo Targets YouTube Channels That Perform or Promote Game Emulation

Extreme Tech

Retro Game Corps, a channel with over half a million subscribers, has received copyright strikes for at least two emulation-related videos.

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MaskLLM: A Learnable AI Method that Facilitates End-to End Training of LLM Sparsity on Large-Scale Datasets

Marktechpost

LLMs, characterized by their massive parameter sizes, often lead to inefficiencies in deployment due to high memory and computational demands. One practical solution is semi-structured pruning, particularly the N: M sparsity pattern, which enhances efficiency by maintaining N non-zero values among M parameters. While hardware-friendly, such as for GPUs, this approach faces challenges due to the vast parameter space in LLMs.

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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How Schneider Electric uses Amazon Bedrock to identify high-potential business opportunities

AWS Machine Learning Blog

This post was co-written with Anthony Medeiros, Manager of Solutions Engineering and Architecture for North America Artificial Intelligence, and Adrian Boeh, Senior Data Scientist – NAM AI, from Schneider Electric. Schneider Electric is a global leader in the digital transformation of energy management and automation. The company specializes in providing integrated solutions that make energy safe, reliable, efficient, and sustainable.

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This AI Paper from KAIST, UCL and KT Investigates the Acquisition and Retention of Factual Knowledge in Large Language Models

Marktechpost

Large language models (LLMs) have garnered significant attention for their ability to understand and generate human-like text. These models possess the unique capability to encode factual knowledge effectively, thanks to the vast amount of data they are trained on. This ability is crucial in various applications, ranging from natural language processing (NLP) tasks to more advanced forms of artificial intelligence.

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Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 1

AWS Machine Learning Blog

Building intelligent agents that can accurately understand and respond to user queries is a complex undertaking that requires careful planning and execution across multiple stages. Whether you are developing a customer service chatbot or a virtual assistant, there are numerous considerations to keep in mind, from defining the agent’s scope and capabilities to architecting a robust and scalable infrastructure.

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AI & Python #26: A Super-Fast Way to Loop in Python

Artificial Corner

Image via Shutterstock Python is known for being a slow programming language. Although it’s a fact that Python is slower than other languages, there are some ways to speed up our Python code. How? Simple, optimize your code. If we write code that consumes little memory and storage, we’ll not only get the job done but also make our Python code run faster.

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The Tumultuous IT Landscape Is Making Hiring More Difficult

After a year of sporadic hiring and uncertain investment areas, tech leaders are scrambling to figure out what’s next. This whitepaper reveals how tech leaders are hiring and investing for the future. Download today to learn more!

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AMD Has Added Frame Generation to Its Adrenalin Drivers

Extreme Tech

The technology is no longer in preview and can be used by anyone with a late-model Radeon GPU.

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LightLLM: A Lightweight, Scalable, and High-Speed Python Framework for LLM Inference and Serving

Marktechpost

Large language models (LLMs) have advanced significantly in recent years. However, its real-world applications are restricted due to substantial processing power and memory requirements. The need to make LLMs more accessible on smaller and resource-limited devices drives the development of more efficient frameworks for model inference and deployment.

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Astronomers Discover Sub-Earth Exoplanet Just 6 Light-Years Away

Extreme Tech

The world orbits Barnard's Star, the closest single-star system to the Sun.

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Microsoft Researchers Unveil RadEdit: Stress-testing Biomedical Vision Models via Diffusion Image Editing to Eliminate Dataset Bias

Marktechpost

Biomedical vision models are increasingly used in clinical settings, but a significant challenge is their inability to generalize effectively due to dataset shifts —discrepancies between training data and real-world scenarios. These shifts arise from differences in image acquisition, changes in disease manifestations, and population variance. As a result, models trained on limited or biased datasets often perform poorly in real-world applications, posing a risk to patient safety.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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New Laser Headset Assesses Stroke Risk In Real Time

Extreme Tech

Though a bit unwieldy, the headset is the first-ever device to predict strokes non-invasively.

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Integrated Value Guidance (IVG): An AI Method that Combines Implicit and Explicit Value Functions Applied to Token-Wise Sampling and Chunk-Level Beam Search

Marktechpost

Integrating human values after model training using Learning-based algorithms requires fine-tuning LLMs, which requires more computational power and is time-consuming. Additionally, it generates biased and undesirable responses by the user. There is a need to develop a model that can efficiently adapt to user preferences in real time by integrating algorithms that can interfere at inference time.

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Intel Updates Its AI Playground Software for Intel-Powered 'AI PCs'

Extreme Tech

It'll work with Lunar Lake, Meteor Lake, or with an Arc GPU.

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