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AI & ML News

"AI & ML News" is a collection of technological notes focused on artificial intelligence and machine learning. It gathers current news and reviews of the latest developments in AI and ML. The feed covers a wide range of topics, including new algorithms, applications, and research. It highlights industry trends and the impact of AI and ML on various sectors of the economy. The materials touch on areas such as neural networks, deep learning, and natural language processing. Examples of AI applications in healthcare, finance, and other industries are examined. The publications will be of interest to both specialists - developers and data analysts, as well as anyone interested in the development of AI technologies. Issues of AI ethics and data privacy are addressed. The feed introduces readers to key players in the AI market - from large companies to promising startups. Information about tools and platforms for AI system development is presented. "AI & ML News" aims to provide objective and up-to-date information on the development of artificial intelligence and machine learning.
RSS Hunter RSS Hunter • Jul 16, 2024

Thread Of Notes

Transformers: Age of Attention

In 2017, researchers introduced the Transformer model in the paper "Attention is All You Need," revolutionizing natural language processing (NLP). Prior models like RNNs and LSTMs processed words sequentially, limiting their ability to handle long sentences, slowing training, and hindering parallel processing. The Transformer solved these issues by using self-attention, allowing the model to focus on important words regardless of their position in a sentence. This made the Transformer faster and more scalable, especially by leveraging parallelization. It eliminated the need for sequential word processing and improved the understanding of complex relationships between words. The model's encoder-decoder architecture efficiently processes input sequences into outputs like translations. Key features like multi-head attention allow the model to capture different aspects of meaning in a sentence simultaneously. The decoder generates translations step-by-step by focusing only on preceding words, ensuring accuracy. This architecture has become the foundation for many state-of-the-art models like BERT and GPT, vastly improving performance in various NLP tasks.
https://hackernoon.com/transformers-age-of-attention?source=rss hackernoon.com
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RSS Hunter RSS Hunter • Aug 27, 2024

A multimodal search solution using NLP, BigQuery and embeddings

The blog discusses the advancement of search technologies beyond text, incorporating images and videos into search capabilities through multimodal embeddings. Traditional enterprise search engines were designed for text-based queries, limiting their ability to handle visual content. By integrating natural language processing (NLP) and multimodal embeddings, it is now possible to perform cross-modal semantic searches, allowing users to search for images and videos as they would with text. The blog demonstrates a system that can perform text-to-image, text-to-video, and combined searches by using Google Cloud Storage for media storage and BigQuery for indexing. A multimodal embedding model is employed to generate embeddings for media files, enabling efficient similarity searches. The architecture supports seamless cross-modal search experiences, making content discovery more intuitive. The user’s text input is converted into an embedding, and a vector search is performed to match the query with the stored media data. Finally, results are presented to the user with the most relevant image or video URIs and their similarity scores. This approach enhances the search experience, unlocking new possibilities for searching visual content.
https://cloud.google.com/blog/products/data-analytics/multimodel-search-using-nlp-bigquery-and-embeddings/ cloud.google.com
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RSS Hunter RSS Hunter • Aug 26, 2024

10 Must-Know Python Libraries for Machine Learning in 2024

As we progress through 2024, machine learning (ML) continues to evolve at a rapid pace. Python, with its rich ecosystem of libraries, remains at the forefront of ML development. In this post, we’ll explore the top 10 Python libraries dominating the ML scene in 2024, how the field has changed since 2020, and the key […]
https://machinelearningmastery.com/10-must-know-python-libraries-for-machine-learning-in-2024/ machinelearningmastery.com
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RSS Hunter RSS Hunter • Aug 26, 2024

AI-Powered GitHub README Generator

The AI-powered README Generator is a new tool designed to help developers create high-quality README files for their GitHub projects. This tool simplifies the documentation process by generating structured, professional-looking README files using basic project information. It offers smart formatting with GitHub-flavored Markdown and provides various templates suitable for different project types. The tool also suggests relevant sections based on the nature of your project and enhances the language for clarity and engagement. By using this tool, developers can save time, improve project visibility, and ensure that their documentation is clear, concise, and consistent. It supports both creating new README files from scratch or refining existing ones by analyzing the current content and suggesting improvements. Users can review and customize the generated content to fit their project’s needs before committing it to their GitHub repository, making it easier for others to understand and contribute to the project. Overall, it’s an effective way to enhance collaboration and showcase projects more professionally.
https://dev.to/shenli3514/ai-powered-github-readme-generator-4pk5 dev.to
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RSS Hunter RSS Hunter • Aug 26, 2024

Boost Your Machine Learning Skills: Free Courses for Math and Statistics

Are you eager to dive into the world of machine learning but feeling a bit overwhelmed by the math and statistics? Don't worry, you're not alone! Many aspiring data scientists find these topics daunting. The good news is, there's a plethora of free online courses that can help you build a solid foundation.Coursera:Machine Learning by Andrew Ng: This legendary course not only introduces you to machine learning concepts but also provides a strong mathematical underpinning. Mathematics for Machine Learning by Imperial College London: If you're seeking a deep dive into the mathematical concepts, this course is a great choice.edX:Introduction to Machine Learning by Microsoft: This course offers a balanced approach, combining machine learning fundamentals with the necessary mathematical knowledge. Fundamentals of Data Science by Columbia University: A broader perspective on data science, including statistics and machine learning, is provided in this course. MIT OpenCourseWare:Introduction to Algorithms: While not strictly about machine learning, this course lays a strong foundation in algorithms and data structures, essential for understanding machine learning concepts. Probability and Random Variables: A deep dive into probability theory is crucial for understanding many machine learning algorithms.Khan Academy:Linear Algebra: A comprehensive resource for learning linear algebra, a fundamental topic in machine learning.Calculus: Another essential mathematical concept, calculus is covered in detail on Khan Academy.Statistics and Probability: A solid understanding of statistics and probability is vital for data analysis and machine learning.Remember: While these courses offer valuable resources, consistent practice and hands-on experience are key to mastering these topics. Start with the basics and gradually increase the complexity as you gain confidence. With dedication and the right resources, you'll be well on your way to becoming a skilled machine learning practitioner.Happy learning!
https://dev.to/sankarsubbu/boost-your-machine-learning-skills-free-courses-for-math-and-statistics-5fo6 dev.to
RSS Hunter RSS Hunter • Aug 25, 2024

Sakana AI’s “AI Scientist”: The Next Einstein or Just a Tool?

In artificial intelligence, a groundbreaking development has emerged that promises to reshape the very process of scientific discovery. In collaboration with the Foerster Lab for AI Research at the University of Oxford and researchers from the University of British Columbia, Sakana AI has introduced “The AI Scientist” – a comprehensive system designed for fully […]
https://www.analyticsvidhya.com/blog/2024/08/ai-scientist/ analyticsvidhya.com
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RSS Hunter RSS Hunter • Aug 25, 2024

Sign Language Detector with Open CV and Python: Hand Gesture Recognition

Hand Gesture Recognition using OpenCV and PythonI have created a YouTube video demonstrating my hand gesture recognition program using OpenCV and Python that can detect sign language gestures! ✋🤖In this project, I did the following: - Set up OpenCV and Python for computer vision - Captured and processed real-time video input - Implemented machine learning for gesture recognition - Detected and interpreted sign language gestures
https://dev.to/rishi_nalem/sign-language-detector-with-open-cv-and-python-hand-gesture-recognition-56le dev.to
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RSS Hunter RSS Hunter • Aug 24, 2024

The top AI deals in Europe this year

In 2024, the European AI sector has shown significant resilience in venture capital funding, with 14 investments exceeding $100 million as of August. This contrasts with the overall challenging landscape for startups, where funding has been difficult to secure. Notably, AI has emerged as a strong area of investment, driven by the high costs associated with developing AI technologies and the intense competition for talent.Key highlights from the top AI deals in Europe this year include: - Wayve: This Cambridge-based startup raised $1.05 billion to enhance its autonomous driving technology, marking the largest single funding round for an AI company in Europe. Wayve focuses on selling its AI technology to car manufacturers rather than producing vehicles itself. - Mistral: A prominent player in building large language models, Mistral has raised over $1 billion through two significant funding rounds of $431 million and $650 million. The company emphasizes open-source technology, appealing to enterprises and developers. - Helsing: This German startup, which focuses on AI for defense applications, secured $484 million. Its technology aims to enhance defense systems and capabilities, particularly in light of geopolitical tensions in Europe. - Poolside: Targeting software developers, Poolside raised $400 million to develop AI tools that streamline software development processes. - DeepL: Known for its AI-driven translation services, DeepL raised $320 million, focusing on the B2B market with around 100,000 business customers. - H: Formerly Holistic AI, this startup raised $220 million as a seed round, aiming to develop AI agents for task automation and decision-making. - Flo Health: The London-based women’s health app raised $200 million, becoming the first purely digital health app to achieve a valuation of over $1 billion. - Pigment: This Parisian startup, which provides enterprise resource planning solutions, raised $145 million, integrating AI into its offerings.Overall, the European AI landscape is characterized by substantial funding rounds and a focus on foundational technologies, with cities like Paris emerging as key hubs for AI development.
https://techcrunch.com/2024/08/24/the-top-ai-deals-in-europe-this-year/ techcrunch.com
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RSS Hunter RSS Hunter • Aug 24, 2024

Substack (YC W18) Is Hiring Machine Learning Engineers

Overview As an ML engineer at Substack, you will play a crucial role in developing and implementing cutting-edge machine learning solutions to enhance our product offerings. You will be part of a dynamic team, collaborating closely with software engineers and data scientists, to bring machine learning models into our codebase and integrate them seamlessly into our products. This role offers an exciting opportunity to shape the future of our technology stack and make a significant impact. Substack’s compensation package includes a market-competitive salary, equity for all full-time roles, and exceptional benefits. Our cash compensation salary range for this role is $185,000 - $240,000. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.Responsibilities - Lead Substack’s thinking about ML adoption and integration of ML tools and techniques - Collaborate with cross-functional teams to identify and define machine learning opportunities that align with our product roadmap - Develop, train, and deploy machine learning models using Python and popular ML frameworks - Leverage off-the-shelf ML tools and systems to accelerate Substack’s ability to incorporate ML functionality into its product and workflows Integrate machine learning models and pipelines into our main JavaScript / TypeScript apps - Optimize and fine-tune ML models for performance, scalability, and efficiency - Design and implement data pipelines for data preprocessing, feature engineering, and model training - Deploy and own integrated product experiences and internal toolsRequirements - 7+ years of relevant experience with data and ML systems - Strong programming skills in Python and experience with Python libraries commonly used in machine learning (e.g. Transformers and Tensorflow) - Solid understanding of machine learning algorithms, deep learning, and statistical modeling - Independent and autonomous. We’re too small to micromanage, and expect that every person at the company owns their work and can be a leader. - Hold yourself and others to a high standard when working on production systems. - Enjoy collaboration with a diverse group of stakeholders while bringing your own unique experience and background to the teamNice to have - Proficiency in Node.js and JavaScript for seamless integration of machine learning models into our codebase - Familiarity with cloud platforms (e.g. AWS or Modal) - Experience with consumer web applications at scale Substack is an equal opportunity employer. All applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, gender identity or transgender status), age, national origin, veteran or disability status. We’re seeking people passionate about enabling independent expression and building a better business model for creators. If you want to see what media, communities, and content can become when unmoored from advertising models, and you have the skills and experience to contribute, we’d love to meet you.
https://grnh.se/d034f1ba5us grnh.se
RSS Hunter RSS Hunter • Aug 24, 2024

AI and Blockchain: An Incompatible Alliance

Blockchain and artificial intelligence (AI) are two rapidly advancing technologies with the potential to revolutionize many sectors. While traditionally considered incompatible, they offer unique strengths: blockchain provides security and transparency, while AI excels at processing vast amounts of data and learning from it. Blockchain ensures the integrity of data, with decentralized, tamper-proof records, while AI brings the power of machine learning and decision-making. When combined, blockchain can secure AI models by encrypting and distributing them, while also providing transparency in AI's decision-making process. This integration can enhance privacy protection, with blockchain controlling access to sensitive data used by AI. The two technologies can revolutionize industries such as logistics, finance, healthcare, and education, offering more efficient systems, personalized services, and greater security. Challenges remain, from legal concerns to technical barriers, but the potential benefits make the synthesis of blockchain and AI a promising step toward a more secure and innovative future.
https://hackernoon.com/ai-and-blockchain-an-incompatible-alliance?source=rss hackernoon.com
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RSS Hunter RSS Hunter • Aug 24, 2024

DBSCAN, Explained in 5 Minutes

DBSCAN is a clustering algorithm that identifies clusters in data based on the density of points, making it useful for handling noise and detecting outliers. Unlike k-means, DBSCAN doesn't require specifying the number of clusters in advance, which makes it advantageous in many situations. The algorithm uses two key parameters: the radius (epsilon) and the minimum number of neighbors (N) required to form a core point. Core points, along with their nearby neighbors, form clusters, while points that don't meet these criteria are labeled as noise or outliers. The implementation of DBSCAN starts with a distance function, often Euclidean, to compute distances between points. The algorithm iterates over all points, grouping them into clusters based on their vicinity to each other. Points that do not have enough neighbors are classified as noise. After implementing DBSCAN, the performance can be checked by comparing it with the results from the sklearn library, which should produce identical clusters. It is important to fine-tune the epsilon and N values, as they heavily influence the clustering results. The article provides an example with synthetic data to visualize the clustering process.
https://towardsdatascience.com/dbscan-explained-in-5-minutes-133f6a9766e4?source=rss----7f60cf5620c9---4 towardsdatascience.com
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RSS Hunter RSS Hunter • Aug 24, 2024

Google DeepMind workers protest over US military and defense contracts

Nearly 200 workers at Google DeepMind, the company’s AI research division, have signed a letter urging the company to terminate its contracts with military organizations.  The May 16 letter, revealed by TIME, highlights growing concern within the organization about the ethical implications of its AI technology being used for digital warfare. The signatories represent around 5% of DeepMind’s workforce, calling out the company’s contracts to supply AI and cloud computing services to various governments, including the Israeli military under Project Nimbus.Google workers worried about their AI being used in warfare.The workers argue such involvement violates Google’s own AI Principles, which state the company will not pursue AI applications that cause “overall harm” or contribute to weaponry and surveillance. Although the letter refrains from mentioning any specific geopolitical conflict, it links to reports alleging that Israeli military operations are using AI for surveillance and targeting. Although DeepMind has historically maintained a policy against using its technology for military purposes, the business has become increasingly close to Google’s broader operations since its acquisition in 2014, leading to closer ties to military contracts. Despite the letter’s demands, including a review of DeepMind’s technology being used by military clients and the establishment of a new governance body, Google has not taken any decisive action. TechRadar Pro has asked the company to comment on the internal letter from staff, but we did not receive an immediate response.  One of the letter’s signatories expressed their dissatisfaction with Google’s response to the complaint to TIME, stating that the company’s statement on Project Nimbus “is so specifically unspecific that we are all none the wiser on what it actually means.”
https://www.techradar.com/pro/google-deepmind-workers-want-the-company-to-drop-its-military-contracts techradar.com
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RSS Hunter RSS Hunter • Aug 23, 2024

ChatGPT-4 vs. Llama 3.1 – Which Model is Better?

Artificial Intelligence has seen remarkable advancements in recent years, particularly in natural language processing. Among the numerous AI language models, two have garnered significant attention: ChatGPT-4 and Llama 3.1. Both are designed to understand and generate human-like text, making them valuable tools for various applications, from customer support to content creation. In this blog, we […]
https://www.analyticsvidhya.com/blog/2024/08/chatgpt-4-vs-llama-3-1/ analyticsvidhya.com
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RSS Hunter RSS Hunter • Aug 23, 2024

How Artificial Intelligence Has Changed The CRM Game

Automation has long been a cornerstone of CRM systems, helping sales, marketing, and customer service teams streamline repetitive tasks. However, the integration of AI has significantly enhanced CRM capabilities, revolutionizing processes like lead management, predictive analytics, and customer service. AI tools in CRM, such as Salesforce’s Einstein, analyze large volumes of data to predict lead conversions, allowing sales teams to focus on high-potential prospects. AI-driven chatbots improve customer service by providing quick, personalized responses and routing complex cases to human agents when necessary. Additionally, AI helps businesses understand their audience better by analyzing customer behavior and creating detailed buyer personas. Sales forecasting has also been improved, as AI can analyze historical and real-time data to predict sales outcomes and identify trends. By enhancing automation with AI, CRM systems now offer more contextually aware and efficient automation of tasks, ultimately boosting productivity. Despite these advancements, human expertise remains crucial for successful AI implementation in CRM, emphasizing the need for upskilling and hiring new talent.
https://hackernoon.com/how-artificial-intelligence-has-changed-the-crm-game?source=rss hackernoon.com
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RSS Hunter RSS Hunter • Aug 23, 2024

This app lets you listen to any book, article or PDF thanks to AI

Text-to-speech company ElevenLabs has released a reader app that offers text-to-speech support for PDFs, ePub files, articles, and more. The app lets you choose from a variety of AI voices for narration and is free to use.Text-to-speech functionality is one of the best accessibility features on smartphones. It’s also handy if you simply want to listen to content instead of reading it (e.g. while driving or running). Thankfully, a new reader app is here that promises to be a major upgrade.ElevenLabs has announced the availability of the ElevenLabs Reader app for Android and iOS, promising to let you listen to anything on the go. More specifically, the developer says you can listen to PDFs, ePub files, text files, articles, newsletters, or other text content. However, it’s worth noting that the app doesn’t support your Kindle library.
https://www.androidauthority.com/elevenlabs-reader-app-3474174/ androidauthority.com
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RSS Hunter RSS Hunter • Aug 23, 2024

What's Going on in Machine Learning? Some Minimal Models

Stephen Wolfram's article explores the inner workings of machine learning through minimal models, aiming to simplify the complexities of AI. He begins by discussing how neural networks are inspired by biological systems but operate using mathematical abstractions. Wolfram highlights the importance of understanding the fundamental processes in machine learning rather than just focusing on outcomes. He uses cellular automata as a simple model to illustrate how complexity can arise from simple rules. By comparing machine learning to these systems, Wolfram suggests that understanding the underlying mechanics can lead to better insights into how AI functions. He also touches on the role of randomness and determinism in training models, arguing that seemingly unpredictable behavior can be traced back to simple, deterministic rules. Wolfram emphasizes the need for new paradigms to better grasp the true nature of machine learning. He also discusses the limitations of current AI models, which often rely heavily on data rather than understanding. Finally, he calls for a deeper exploration of minimal models to uncover the core principles governing machine learning, which could lead to more robust and interpretable AI systems.
https://writings.stephenwolfram.com/2024/08/whats-really-going-on-in-machine-learning-some-minimal-models/ writings.stephenwolfram.com
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RSS Hunter RSS Hunter • Aug 23, 2024

DeepMind workers sign letter in protest of Google’s defense contracts

At least 200 workers at DeepMind, Google’s AI R&D division, are displeased with Google’s reported defense contracts — and according to Time, they circulated a letter internally back in May to say as much. The letter, dated May 16, says the undersigned are concerned by “Google’s contracts with military organizations,” citing articles about the tech […]
https://techcrunch.com/2024/08/22/deepmind-workers-sign-letter-in-protest-of-googles-defense-contracts/ techcrunch.com
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RSS Hunter RSS Hunter • Aug 23, 2024

Train/Fine-Tune Segment Anything 2 (SAM 2) in 60 Lines of Code

SAM2 (Segment Anything 2) by Meta is a versatile image segmentation model trained on an extensive dataset of 11 million images and 11 billion masks, making it highly effective for a wide range of segmentation tasks. While SAM2 can segment common objects well, it may underperform on rare or domain-specific tasks, necessitating fine-tuning to improve performance on specific datasets. This tutorial outlines how to fine-tune SAM2 for custom tasks in just 60 lines of code. The process involves downloading SAM2, preparing a dataset, and using a simple script to load images, segment masks, and select random points within those masks. The fine-tuning focuses on training the mask decoder and, optionally, the prompt encoder while freezing the image encoder. The tutorial also covers setting up the optimizer, employing mixed precision training, and running a training loop with custom loss functions to refine the model. The final step includes saving the fine-tuned model and using it for inference on new images, demonstrating the practical application of SAM2 in specialized segmentation tasks.
https://towardsdatascience.com/train-fine-tune-segment-anything-2-sam-2-in-60-lines-of-code-928dd29a63b3?source=rss----7f60cf5620c9---4 towardsdatascience.com
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RSS Hunter RSS Hunter • Aug 23, 2024

Turn your napkin doodles into high art with this AI image generator

AI image generators are rapidly advancing, with several platforms introducing major updates. Ideogram has recently launched Ideogram 2.0, featuring significant improvements and new features, including an iOS app and a vast searchable library of over a billion user-generated images. This version offers users greater control over the AI-generated images, with a variety of distinct styles such as Realistic, which produces lifelike images, and Design, which excels in text accuracy within images. Additional styles include 3D, Anime, and General, each catering to different creative needs. Ideogram 2.0 has also enhanced its Magic Prompt and Describe tools, allowing for more detailed prompt expansion and image description generation. The launch includes a beta API, enabling integration with other apps, similar to how DALL-E and Flux are embedded in other platforms. With these updates, Ideogram 2.0 aims to compete with major players like OpenAI’s DALL-E, promising high-quality, photorealistic images with readable text.
https://www.techradar.com/computing/artificial-intelligence/turn-your-napkin-doodles-into-high-art-with-this-ai-image-generator techradar.com
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RSS Hunter RSS Hunter • Aug 23, 2024

Announcing the Jamba 1.5 Model Family from AI21 Labs on Vertex AI

AI21 Labs has introduced the Jamba 1.5 Model Family, which is now available in public preview on Google Cloud's Vertex AI Model Garden. The family includes two models: Jamba 1.5 Mini, designed for efficient and lightweight tasks like customer support and text generation, and Jamba 1.5 Large, which excels in advanced reasoning tasks such as financial analysis. Both models feature a 256K context window and use the Mamba-Transformer architecture, offering efficient processing and advanced developer features like function calling, Retrieval-Augmented Generation (RAG) optimizations, and structured JSON output.These models are tailored for enterprise applications, particularly in areas such as customer service, financial analysis, and content creation. For instance, they can summarize lengthy documents, extract insights from financial data, and generate high-quality content. The Jamba 1.5 models are part of Google Cloud's broader commitment to an open and flexible AI ecosystem, providing enterprise users with the ability to build solutions that best meet their needs.Available on Vertex AI, these models expand the platform's offerings, which include over 150 models, enabling users to choose the best tools for their projects. Vertex AI supports easy experimentation, customization, and deployment of these models, allowing for optimized performance, cost management, and secure deployment. Developers can access these models through simple API calls and deploy them using Google Cloud’s managed infrastructure, which offers robust security and compliance features.Getting started with the Jamba 1.5 models is straightforward, with users able to select and enable the models directly from Vertex AI Model Garden or Google Cloud Marketplace. Google Cloud continues to collaborate with partners like AI21 Labs to deliver cutting-edge AI capabilities, ensuring developers have access to the latest advancements in AI technology.
https://cloud.google.com/blog/products/ai-machine-learning/jamba-1-5-model-family-from-ai21-labs-is-now-available-on-vertex-ai/ cloud.google.com
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RSS Hunter RSS Hunter • Aug 23, 2024

Document Extraction is GenAI’s Killer App

The article discusses the evolution and impact of generative AI (GenAI) in automating complex office tasks, particularly document extraction. The author reflects on their experience as a Machine Learning Engineer at LinkedIn, where accurately interpreting job titles across various languages and regions was a challenging task. With the advent of large language models (LLMs) like GPT-4, tasks that were once difficult, such as understanding and standardizing résumés, have become trivial. The real potential of GenAI lies in automating office work that involves extracting insights from documents, a task that constitutes a significant portion of global GDP. Examples include expense management, healthcare claim adjudication, and loan underwriting. Although LLMs are known to hallucinate in some contexts, they excel at reasoning about text when grounded in specific input documents. The key to successful document extraction using LLMs is clean text conversion and robust schema design, which ensure consistent and accurate outputs. The author highlights the importance of proper text extraction, which involves handling complex formatting and annotations. They share their experience of building Docupanda.io, a SaaS solution designed to address the challenges of document understanding by generating clean text representations and adhering to predefined schemas. The article emphasizes that defining these schemas is crucial and that AI can assist in refining them through iterative feedback. Finally, the author encourages exploring the use of LLMs for regularizing document processing, suggesting that GenAI’s true "killer app" is its ability to transform document-based office work.
https://towardsdatascience.com/document-extraction-is-genais-killer-app-9e9c816e6caf?source=rss----7f60cf5620c9---4 towardsdatascience.com
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RSS Hunter RSS Hunter • Aug 22, 2024

Harmonyze wants to build AI agents to help franchisors make sense of unstructured data

For some businesses, there is a clear path to growth that doesn’t involve acquiring other companies or expanding organically: franchising. The U.S. has more than 800,000 franchise businesses, according to Statista, and that number is predicted to keep growing year over year. But franchising a business — licensing a business model and brand to an […]
https://techcrunch.com/2024/08/22/harmonyze-built-ai-agents-that-sit-between-franchisors-and-their-franchisees/ techcrunch.com
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RSS Hunter RSS Hunter • Aug 22, 2024

Advancing System Reliability: Meta's AI-Driven Approach to Root Cause Analysis

Meta, recently, shared how they are enhancing its system reliability through advanced investigation tools, including the AI-assisted Hawkeye, which aids in debugging machine learning workflows. By integrating Artificial Intelligence, Meta has developed a new investigation system that combines heuristic-based retrieval with large language model (LLM) ranking to assist in root cause analysis.
https://www.infoq.com/news/2024/08/meta-rca-ai-driven/ infoq.com
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RSS Hunter RSS Hunter • Aug 22, 2024

LLM-Powered DevOps Assistant Clio Launches to Help Engineers Manage Cloud Infrastructure

Acorn, a company founded to help organisations implement AI-based technology solutions, has recently introduced Clio, an AI-powered command-line assistant designed to help engineers manage DevOps workflows.In a blog post and a YouTube live stream, Acorn describes Clio as a "slightly grumpy but friendly assistant" which can handle various DevOps-related tasks through natural language.
https://www.infoq.com/news/2024/08/ai-devops-clio/ infoq.com
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RSS Hunter RSS Hunter • Aug 22, 2024

Introducing New Features on Codest: Generate Flutter and React Native Apps!

In our recent newsletter, we introduced Codest, an AI tool that generates NextJS apps from images. Building on its success, our R&D team has expanded Codest's capabilities to now include the generation of Flutter and React Native apps from images. We've documented our progress in two previous blog articles and are excited to announce that these new features are now available in our Proof of Concept (PoC).What's New? - Flutter App Generation: Codest can now generate high-quality, modular Flutter code from images, with clear separation between layout and data. - React Native App Generation: Similar to the Flutter integration, Codest also generates structured and reusable React Native code.Why Use Codest? Codest has been shown to reduce development time by up to 20%, providing developers with clean, modular code that helps streamline the development process for both mobile and web apps.We invite you to check out three short videos that showcase Codest in action, demonstrating how it can generate functional apps from images for React Native, Flutter, and Next.js.
https://dev.to/codelink/introducing-new-features-on-codest-generate-flutter-and-react-native-apps-1dme dev.to
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RSS Hunter RSS Hunter • Aug 22, 2024

Dream Machine 1.5 Catches Sora and other rival AI video makers napping

Luma Labs has significantly upgraded its Dream Machine AI video generator with the release of Dream Machine 1.5, raising the bar for realism and responsiveness to user prompts. This update poses a challenge to competitors, particularly OpenAI, which has yet to publicly release its Sora AI video model. Dream Machine 1.5 offers faster video generation, producing five seconds of high-quality video in about two minutes, and showcases improved realism, smoother motion, and better text rendering. These advancements make it a valuable tool for content creators and marketers under tight deadlines.Despite the competition from other AI video generators like Runway, Stability AI, and Bytedance's Jimeng, Dream Machine 1.5 stands out due to its availability and performance. This launch marks a significant development in the AI-generated video landscape, potentially transforming industries like entertainment, advertising, and journalism by enabling quick and easy creation of high-quality visual content.
https://www.techradar.com/computing/artificial-intelligence/dream-machine-15-catches-sora-and-other-rival-ai-video-makers-napping techradar.com
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RSS Hunter RSS Hunter • Aug 22, 2024

Microsoft’s contentious AI-powered Recall system finally has an ETA

After weeks of delays, Microsoft has shared that Recall for Copilot Plus PCs will open public testing in October. The controversial screenshot-mining system faced harsh security and privacy concerns when first announced.AI and controversy go hand in hand, and one of the more contentious developments occurred earlier this year, when Microsoft revealed its plan to introduce Recall for Copilot Plus PCs. The system would continually take screenshots while you use your PC, process that imagery with AI, and then allow you search through them to reference later. After months of waiting, we’re finally learning when Microsoft intends to open up Recall to its first public testers.Recall immediately drew concern from privacy advocates, fearing that the mere existence of this massive record of everything you did on your PC represented an unnecessary privacy liability — just think how exposed you’d be if anyone ever got access to that. And indeed, early analysis by an independent researcher only raised anxiety about how Microsoft planned to implement Recall.
https://www.androidauthority.com/microsoft-recall-testing-3474077/ androidauthority.com
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RSS Hunter RSS Hunter • Aug 22, 2024

McAfee’s Deepfake Detector keeps it real for Lenovo AI PCs

Deepfake videos, which use AI to mimic real people, pose significant cybersecurity risks, particularly by deceiving people with fake content of celebrities and public figures. To combat this, McAfee has partnered with Lenovo to introduce the Deepfake Detector, a tool designed to identify and flag deepfake videos on select Lenovo AI PCs. This tool, trained on 200,000 video samples, operates locally on devices with a neural processing unit (NPU), ensuring privacy and real-time detection without needing cloud access. Initially available in the U.S., UK, and Australia, the detector is included in new Lenovo AI PCs with a 30-day trial, followed by a $10 annual subscription. The collaboration between McAfee and Lenovo aims to enhance digital safety, though the exclusivity regarding Intel chips remains unclear. Additionally, McAfee offers a Smart AI Hub at McAfee.ai for users to analyze videos for deepfakes and learn about AI-driven scams.
https://www.techradar.com/computing/artificial-intelligence/mcafees-deepfake-detector-keeps-it-real-for-lenovo-ai-pcs techradar.com
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RSS Hunter RSS Hunter • Aug 22, 2024

Telecom that enabled Biden deepfake scam will pay FCC $1M

Early this year, AI-powered fake audio of President Biden reached voters in New Hampshire. The FCC struck back swiftly, identifying the perpetrator as the Texas-based Life Corporation, which has been behind similar scams over the years, and whacked them and an associated individual with a $6 million fine. But the scammers also enlisted the help […]
https://techcrunch.com/2024/08/21/telecom-that-enabled-biden-deepfake-scam-will-pay-fcc-1m/ techcrunch.com
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RSS Hunter RSS Hunter • Aug 22, 2024

Gmail’s ‘Help Me Write’ Feature Can Now Polish Up Your Emails With AI

Google is expanding its AI-powered writing assistance in Gmail through features powered by Gemini under the "Help me write" shortcut. The latest addition is a "Polish" option that refines email drafts, typically making them more formal, and is available on both mobile and web platforms. Additionally, when composing emails of at least 12 words on iOS and Android, users can access options like Polish, Formalize, Elaborate, Shorten, and Write a new draft by swiping on the "Refine my draft" prompt. These features are exclusive to subscribers of Google One's AI Premium plan or organizations with specific Gemini add-ons for education and business. However, there is skepticism about the practicality and efficiency of these tools, with some questioning whether they genuinely save time or improve the quality of email communication.
https://lifehacker.com/tech/two-new-gemini-for-gmail-features lifehacker.com
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RSS Hunter RSS Hunter • Aug 22, 2024

D-ID launches an AI video translation tool that includes voice cloning and lip sync

AI video creation platform D-ID is the latest company to ship a tool for translating videos into other languages using AI technologies. However, in this case, D-ID also clones the speaker’s voice and changes their lip movements to match the translated words as part of the AI editing process. The technology stems from D-ID’s earlier […]
https://techcrunch.com/2024/08/21/d-id-launches-an-ai-video-translation-tool-that-includes-voice-cloning-and-lip-sync/ techcrunch.com
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RSS Hunter RSS Hunter • Aug 22, 2024

7 AI PPT Makers For Your Next Office Presentation

You might be in your final year of college, striving to make your capstone project stand out, or a working professional navigating the demands of daily meetings and client presentations. In both scenarios, you understand how crucial a strong first impression is, whether it’s in a professional setting or a personal encounter. A well-designed […]
https://www.analyticsvidhya.com/blog/2024/08/ai-ppt-maker/ analyticsvidhya.com
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RSS Hunter RSS Hunter • Aug 22, 2024

Run your AI inference applications on Cloud Run with NVIDIA GPUs

Google Cloud has introduced NVIDIA L4 GPU support for Cloud Run, now in preview, enabling developers to perform real-time AI inference with ease. This upgrade is particularly beneficial for applications utilizing open generative AI models, such as Google's Gemma and Meta's Llama. Key features include fast autoscaling, scale-to-zero, and pay-per-use pricing, making Cloud Run ideal for handling variable user traffic and cost optimization.With this new capability, developers can deploy lightweight models for tasks like custom chatbots and document summarization, or more compute-intensive applications like image recognition and 3D rendering. The NVIDIA GPUs enhance performance by speeding up AI inference processes, offering low latency and efficient scaling, with Cloud Run's infrastructure managing the underlying complexities.Early adopters, like L’Oreal and Chaptr, have praised the GPU integration for its low startup times, scalability, and ease of use. The GPU support is currently available in the US-central1 region, with plans to expand to Europe and Asia by year-end.To deploy a service with NVIDIA GPUs on Cloud Run, developers can specify GPU requirements via command-line or the Google Cloud console. Additionally, Cloud Run now supports functions with GPU attachments, simplifying event-driven AI inference tasks.
https://cloud.google.com/blog/products/application-development/run-your-ai-inference-applications-on-cloud-run-with-nvidia-gpus/ cloud.google.com
RSS Hunter RSS Hunter • Aug 21, 2024

Openmart wants to make it easier for enterprises to sell to local businesses

In 2020, Kathryn Wu launched a side hustle while she was working as a product engineer at Pinterest. Wu started a milk tea company, OhTea, with the hopes of connecting with local grocery stores and gift shops to get them to carry the tea. She quickly realized how difficult it was to not only be […]
https://techcrunch.com/2024/08/21/openmart-wants-to-make-it-easier-for-enterprises-to-sell-to-local-businesses/ techcrunch.com
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RSS Hunter RSS Hunter • Aug 21, 2024