Analytics Vidhya

AUGUST 18, 2024

Introduction We have said au revoir to the Olympic Games Paris 2024, and the next will be held after 4 years, but the development by Google DeepMind may signal a new era in sports and robotics development. I recently came across a fascinating research paper (Achieving Human-Level Competitive Robot Table Tennis) by Google DeepMind that […] The post Will this Google Deepmind Robot Play Table Tennis in the 2028 Olympics?

Robotics 279

Robotics Machine Learning Artificial Intelligence Artificial Intelligence 279

Marktechpost

AUGUST 18, 2024

Vision-language models (VLMs) have gained significant attention due to their ability to handle various multimodal tasks. However, the rapid proliferation of benchmarks for evaluating these models has created a complex and fragmented landscape. This situation poses several challenges for researchers. Implementing protocols for numerous benchmarks is time-consuming, and interpreting results across multiple evaluation metrics becomes difficult.

Python 122

Python Categorization Data Quality ML 122

Analytics Vidhya

AUGUST 18, 2024

In this episode of Leading with Data, we chat with Gaurav Agarwal, the founder and CEO of RagaAI, about the exciting world of generative AI. As this technology continues to reshape industries, RagaAI is focused on making sure it does so reliably. Gaurav shares his journey, the challenges he’s faced, and how RagaAI is helping […] The post Gaurav Agarwal’s Blueprint for Success with RagaAI appeared first on Analytics Vidhya.

Generative AI 245

Generative AI AI AI Responsible AI 245

Marktechpost

AUGUST 18, 2024

Language models (LMs) exhibit improved performance with increased size and training data, yet the relationship between model scale and hallucinations remains unexplored. Defining hallucinations in LMs presents challenges due to their varied manifestations. A new study from Google Deepmind focuses on hallucinations where correct answers appear verbatim in training data.

Auto-complete 119

Auto-complete Natural Language Processing ML AI 119

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

Artificial Lawyer

AUGUST 18, 2024

LexisNexis has clarified how its new Protégé Legal AI Assistant connects to the holiest of holies, AKA your law firm’s Document Management System (DMS), to.

AI 122

AI AI 122

Machine Learning Mastery

AUGUST 18, 2024

Preparing categorical data correctly is a fundamental step in machine learning, particularly when using linear models. One Hot Encoding stands out as a key technique, enabling the transformation of categorical variables into a machine-understandable format. This post tells you why you cannot use a categorical variable directly and demonstrates the use One Hot Encoding in […] The post One Hot Encoding: Understanding the “Hot” in Data appeared first on MachineLearningMastery.com.

Categorization 82

Categorization Machine Learning Data Science 82

Marktechpost

AUGUST 18, 2024

Deep learning models typically represent knowledge statically, making adapting to evolving data needs and concepts challenging. This rigidity necessitates frequent retraining or fine-tuning to incorporate new information, which could be more practical. The research paper “Towards Flexible Perception with Visual Memory” by Geirhos et al. presents an innovative solution that integrates the symbolic strength of deep neural networks with the adaptability of a visual memory database.

Deep Learning 105

Deep Learning Neural Network Large Language Models Continuous Learning 105

TheSequence

AUGUST 18, 2024

Next Week in The Sequence: Edge 423: We explore the fundamentals of state space models including the fmaous S4 paper. The tech section provides an overview of NVIDIA’s NIM framework. Edge 424: We dive into the DeepMind’s amazing AlphaProof and AlphaGeometry-2 that achieved silver medal in the latest international math olympiad. You can subscribe to The Sequence below: TheSequence is a reader-supported publication.

AI 59

AI AI OpenAI LLM 59

Marktechpost

AUGUST 18, 2024

Future reward estimation is crucial in RL as it predicts the cumulative rewards an agent might receive, typically through Q-value or state-value functions. However, these scalar outputs lack detail about when or what specific rewards the agent anticipates. This limitation is significant in applications where human collaboration and explainability are essential.

Explainability 102

Explainability Neural Network ML AI 102

Advertisement

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

Machine Learning Research at Apple

AUGUST 18, 2024

Self-supervised features are typically used in place of filter-bank features in speaker verification models. However, these models were originally designed to ingest filter-banks as inputs, and thus, training them on self-supervised features assumes that both feature types require the same amount of learning for the task. In this work, we observe that pre-trained self-supervised speech features inherently include information required for a downstream speaker verification task, and therefore, we

52

52

Marktechpost

AUGUST 18, 2024

Large language models (LLMs) have considerably altered the landscape of natural language processing, enabling machines to understand and generate human language much more effectively than ever. Normally, these models are pre-trained on huge and parallel corpora and then fine-tuned to connect them to human tasks or preferences. Therefore, This process has led to great advances in the field that the LLMs have become very useful tools for different applications, from language translation to sentime

LLM 64

LLM Large Language Models Natural Language Processing Big Data 64

Robot Writers AI

AUGUST 18, 2024

RobotWritersAI.com is playing hooky. We’ll be back Sept. 2, 2024 with fresh news and analysis on the latest in AI-generated writing. Never Miss An Issue Join our newsletter to be instantly updated when the latest issue of Robot Writers AI publishes We respect your privacy. Unsubscribe at any time -- we abhor spam as much as you do. The post Gone Fishin’ appeared first on Robot Writers AI.

Robotics 52

Robotics AI AI 52

Marktechpost

AUGUST 18, 2024

Large Language Models (LLMs) have gained significant attention due to their remarkable performance across various tasks, revolutionizing research paradigms. However, the training process for these models faces several challenges. LLMs depend on static datasets and undergo long training periods, which require a lot of computational resources. For example, training the LLaMA 65B model took 21 days using 2048 A100 GPUs with 80GB of RAM.

Large Language Models 64

Large Language Models NLP Data Quality ML 64

Advertisement

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

Marktechpost

AUGUST 18, 2024

LLMs have revolutionized artificial intelligence, particularly natural language processing and software engineering. Models useful for specific tasks such as generating, understanding, and translating text are being integrated into many applications. Because of their nature, LLMs, like OpenAI’s ChatGPT and GPT-4, have interacted extensively with developers’ AI-driven task conduct.

Large Language Models 59

Large Language Models Software Engineer LLM OpenAI 59

Marktechpost

AUGUST 18, 2024

In the field of Natural Language Processing (NLP), Retrieval Augmented Generation, or RAG, has attracted much attention lately. Breaking down documents into chunks, embedding those chunks, storing the embeddings, and then finding the closest match and adding it to the query context when receiving a query is a seemingly straightforward process. It would seem simple to get RAG to function well regularly in production, as many RAG components are already easily accessible, such as embedding models f

Auto-complete 59

Auto-complete Natural Language Processing LLM NLP 59

Marktechpost

AUGUST 18, 2024

Tasks like extracting data, creating market maps, and sorting through transcripts and board packs prevent analysts from using the first principles of thinking to generate alpha. Airtable, Dropbox, and email are just a few examples of the internal data silos they face. At the same time, external sources include websites, SEC filings, and private data feeds from companies like S&P.

AI 59

AI AI Data Extraction Automation 59

Marktechpost

AUGUST 18, 2024

Language model alignment is quite important, particularly in a subset of methods from RLHF that have been applied to strengthen the safety and competence of AI systems. Language models are deployed in many applications today, and their outputs can be harmful or biased. Inherent human preference alignment under RLHF ensures that their behaviors are ethical and socially applicable.

Automation 59

Automation AI Development AI Developer ML 59

Advertisement

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

Marktechpost

AUGUST 18, 2024

Extended Reality (XR) technology transforms how users interact with digital environments, blending the physical and virtual worlds to create immersive experiences. XR devices are equipped with advanced sensors that capture rich streams of user data, enabling personalized and context-aware interactions. The rapid evolution of this field has prompted researchers to explore the integration of artificial intelligence (AI) into XR environments, aiming to enhance productivity, communication, and user

AI 59

AI AI Artificial Intelligence Artificial Intelligence 59

Marktechpost

AUGUST 18, 2024

A Large Language Model (LLM) is an advanced type of artificial intelligence designed to understand and generate human-like text. It’s trained on vast amounts of data, enabling it to perform various natural language processing tasks, such as answering questions, summarizing content, and engaging in conversation. LLMs are revolutionizing education by serving as chatbots that enrich learning experiences.

Chatbots 64

Chatbots AI Tools LLM Natural Language Processing 64