AI News

OCTOBER 10, 2024

While AI improves the detection of cybersecurity threats, it simultaneously ushers in more advanced challenges. Research from Keeper Security finds that, despite the implementation of AI-related policies, many organisations remain inadequately prepared for AI-powered threats. 84% of IT and security leaders find AI-enhanced tools have exacerbated the challenge of detecting phishing and smishing attacks, which were already significant threats.

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Analytics Vidhya

OCTOBER 10, 2024

Introduction What if machines could make their own decisions, solve problems, and adapt to new situations just like we do? This would potentially lead to a world where artificial intelligence becomes not just a tool but a collaborator. That’s exactly what AI agents aim to achieve! These smart systems are designed to understand their surroundings, […] The post 5 Types of AI Agents that you Must Know About appeared first on Analytics Vidhya.

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AI News

OCTOBER 10, 2024

China Telecom, one of the country’s state-owned telecom giants, has created two LLMs that were trained solely on domestically-produced chips. This breakthrough represents a significant step in China’s ongoing efforts to become self-reliant in AI technology, especially in light of escalating US limitations on access to advanced semiconductors for its competitors.

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AI Weekly

OCTOBER 10, 2024

Welcome Interested in sponsorship opportunities? Join the AI conversation and transform your advertising strategy with AI weekly sponsorship aiweekly.co In the News Google's Nobel prize winners stir debate over AI research Google has been at the forefront of AI research, but has been forced on the defensive as it tackles competitive pressure from Microsoft-backed (MSFT.O), opens new tab OpenAI and mounting regulatory scrutiny from the U.S Department of Justice. reuters.com Sponsor Personaliz

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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

Analytics Vidhya

OCTOBER 10, 2024

Introduction Learning is a continuous journey, whether you’re human or an AI model. However, one question that often comes up is, can these AI models learn themselves just like humans do? As per the recent developments – They can. To understand this in a better way, let’s go back to our college days when C++, […] The post Top 4 Agentic AI Design Patterns for Architecting AI Systems appeared first on Analytics Vidhya.

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Analytics Vidhya

OCTOBER 10, 2024

Introduction Language-Integrated Data Analysis (LIDA) is a powerful tool designed to automate visualization creation, enabling the generation of grammar-agnostic visualizations and infographics. LIDA addresses several critical tasks: interpreting data semantics, identifying appropriate visualization goals, and generating detailed visualization specifications.

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Unite.AI

OCTOBER 10, 2024

ApertureData , a company at the forefront of multimodal AI data management, has raised $8.25 million in an oversubscribed seed round to drive the development and expansion of its groundbreaking platform, ApertureDB. The round was led by TQ Ventures with participation from Westwave Capital , Interwoven Ventures , and a number of angel investors. The funding will allow ApertureData to scale its operations and launch its new cloud-based service, ApertureDB Cloud, a tool designed to simplify and acc

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Analytics Vidhya

OCTOBER 10, 2024

Introduction When attending a job interview or hiring for a large company, reviewing every CV in detail is often impractical due to the high volume of applicants. Instead, leveraging CV data extraction to focus on how well key job requirements align with a candidate’s CV can lead to a successful match for both the employer […] The post CV Data Extraction: Essential Tools and Methods for Recruitment appeared first on Analytics Vidhya.

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Unite.AI

OCTOBER 10, 2024

Rohit Aggarwal is Chief Operating Officer at DecisionNext , a leading AI platform that enables companies to optimize the buying or selling of commodities at the best possible time and price. He leverages a strong background in supply chain and product management as well as experience directly leading very large teams to execute complex multi-disciplinary projects and deliver business results.

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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?

Business Intelligence

Analytics Vidhya

OCTOBER 10, 2024

Introduction Computing square root is a critical concept in mathematics and within this programming language one is able to embark on this basic computation in a very simple and efficient manner. Whether you’re involved in an experiment, simulations, data analysis or using machine learning, calculating square roots in Python is crucial. In this guide, you […] The post Python Square Root appeared first on Analytics Vidhya.

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Unite.AI

OCTOBER 10, 2024

OpenAI is currently facing significant financial challenges. For example, in 2023, it was reported that to maintain its infrastructure and run its flagship product, OpenAI pays around $700,000 per day. However, in 2024, the company's total spending on inference and training could reach $7 billion , driven by increasing computational demands. This large operational cost highlights the immense resources required to maintain advanced AI systems.

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Analytics Vidhya

OCTOBER 10, 2024

Introduction AI agents are all set to become the next revolution in the GenAI Paradigm. The modern-day agent’s ability to harness AI to think and reason has enabled humans to truly automate routine tasks. The creation of AI agent frameworks and architectures like AutoGen, Crew AI, LangChain, etc, have come in handy in pushing the […] The post 5 Real-Life Use Cases of AI Agents for Day-to-Day Work appeared first on Analytics Vidhya.

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Unite.AI

OCTOBER 10, 2024

Internal financial projections from OpenAI reveal a high-stakes strategy that pairs aggressive revenue targets with substantial projected losses, according to a recent report by The Information. The company's plans highlight both the immense potential and significant risks in the rapidly evolving AI sector. OpenAI Projects Massive Revenue Growth OpenAI, the company behind ChatGPT, aims to increase its annual revenue from $1 billion in 2023 to $100 billion by 2029.

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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

AI

Machine Learning Research at Apple

OCTOBER 10, 2024

Recent advancements in Large Language Models (LLMs) have sparked interest in their formal reasoning capabilities, particularly in mathematics. The GSM8K benchmark is widely used to assess the mathematical reasoning of models on grade-school-level questions. While the performance of LLMs on GSM8K has significantly improved in recent years, it remains unclear whether their mathematical reasoning capabilities have genuinely advanced, raising questions about the reliability of the reported metrics.

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Marktechpost

OCTOBER 10, 2024

Developing therapeutics is costly and time-consuming, often taking 10-15 years and up to $2 billion, with most drug candidates failing during clinical trials. A successful therapeutic must meet various criteria, such as target interaction, non-toxicity, and suitable pharmacokinetics. Current AI models focus on specialized tasks within this pipeline, but their limited scope can hinder performance.

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Towards AI

OCTOBER 10, 2024

Last Updated on October 12, 2024 by Editorial Team Author(s): Dr. Alessandro Crimi Originally published on Towards AI. Can a Foundation Model Revolutionize Time Series Forecasting, or are we stuck with Granger causality? This member-only story is on us. Upgrade to access all of Medium. What is the effect and the cause? (royalty-free picture from www.pexels.com) For causality, we define the influence by which one event, process, state, or contributes to the production of another event, process, s

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Marktechpost

OCTOBER 10, 2024

Researchers are investigating whether large language models (LLMs) can move beyond language tasks and perform computations that mirror traditional computing systems. The focus has shifted towards understanding whether an LLM can be computationally equivalent to a universal Turing machine using only its internal mechanisms. Traditionally, LLMs have been used primarily for natural language processing tasks like text generation, translation, and classification.

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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.

Business Intelligence

Towards AI

OCTOBER 10, 2024

Last Updated on October 12, 2024 by Editorial Team Author(s): Vladyslav Fliahin Originally published on Towards AI. Introduction Source: Image generated by the author using AI (Flux AI) Did you know that businesses receive thousands of customer reviews daily, each containing valuable insights? Yet, making sense of this data and processing it is a challenging task.

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Marktechpost

OCTOBER 10, 2024

The field of multimodal artificial intelligence (AI) revolves around creating models capable of processing and understanding diverse input types such as text, images, and videos. Integrating these modalities allows for a more holistic understanding of data, making it possible for the models to provide more accurate and contextually relevant information.

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NVIDIA

OCTOBER 10, 2024

Half of the world’s population will experience a mental health disorder — but the median number of mental health workers per 100,000 people is just 13, according to the World Health Organization. To help tackle this disparity — which can vary by over 40x between high-income and low-income countries — a Madrid-based startup is offering therapists AI tools to improve the delivery of mental health services.

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Marktechpost

OCTOBER 10, 2024

Artificial intelligence has made remarkable strides with the development of Large Language Models (LLMs), significantly impacting various domains, including natural language processing, reasoning, and even coding tasks. As LLMs grow more powerful, they require sophisticated methods to optimize their performance during inference. Inference-time techniques and strategies used to improve the quality of responses generated by these models at runtime have become crucial.

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Towards AI

OCTOBER 10, 2024

Last Updated on October 12, 2024 by Editorial Team Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week we discuss the hottest trend in AI: Model Distillation, along with some interesting articles on RAG, Llama 3.2, and Bayesian methods. What’s AI Weekly This week, in my other newsletter, the High Learning Rate newsletter, I explore an essential technique in LLMs: model distillation.

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Marktechpost

OCTOBER 10, 2024

Advanced Micro Devices (AMD) has made a bold move in the competitive AI hardware market by launching its new MI325x AI chip, a powerful accelerator aimed squarely at rivaling Nvidia’s latest Blackwell series. The new chip, announced on October 10, 2024, marks AMD’s latest effort to expand its share in the lucrative artificial intelligence computing sector, where Nvidia has maintained a stronghold for years.

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databricks

OCTOBER 10, 2024

Today, we are excited to announce the general availability of Databricks Assistant Autocomplete on all cloud platforms. Assistant Autocomplete provides personalized AI-powered code.

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Marktechpost

OCTOBER 10, 2024

In today’s tech-driven world, data science and machine learning are often used interchangeably. However, they represent distinct fields. This article explores the differences between data science vs. machine learning , highlighting their key functions, roles, and applications. What is Data Science? Data science is the practice of extracting insights from large datasets.

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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.

Generative AI

Artificial Lawyer

OCTOBER 10, 2024

This week’s product walk through is with Legau, which is a multi-capability legal drafting system leveraging genAI and designed to support lawyers with all types.

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Marktechpost

OCTOBER 10, 2024

Large vision-language models have emerged as powerful tools for multimodal understanding, demonstrating impressive capabilities in interpreting and generating content that combines visual and textual information. These models, such as LLaVA and its variants, fine-tune large language models (LLMs) on visual instruction data to perform complex vision tasks.

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TheSequence

OCTOBER 10, 2024

Created Using Ideogram Grounding large foundation models such as LLMs on factual data is one of the biggest challenge of the current wave of AI systems. From reducing hallucinations to expanding the use cases for LLMs to mission critical applications, validating LLM outputs with trustworthy data is rapidly becoming one of the most important building blocks of LLM applications.

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