Analytics Vidhya

AUGUST 25, 2024

Introduction Sitting in front of a desktop, away from you, is your own personal assistant, she knows the tone of your voice, answers to your questions and is even one step ahead of you. This is the beauty of Amazon Alexa, a smart speaker that is driven by Natural Language Processing and Artificial Intelligence. But […] The post How Amazon Alexa Works Using NLP appeared first on Analytics Vidhya.

NLP 238

NLP Natural Language Processing Artificial Intelligence Artificial Intelligence 238

Ehud Reiter

AUGUST 25, 2024

Many people in NLP seem to think that you need to work with the latest and trendiest technology in order to be relevant, both in research and in applications. I think this is a narrow view of the world – sometimes the latest tech is just what is needed, but sometimes it is not. LSTMs do not work in data-to-text Let me start with an example from the late 2010s.

BERT 135

BERT NLP Natural Language Processing Prompt Engineering 135

Analytics Vidhya

AUGUST 25, 2024

Introduction Assessing a machine learning model isn’t just the final step—it’s the keystone of success. Imagine building a cutting-edge model that dazzles with high accuracy, only to find it crumbles under real-world pressure. Evaluation is more than ticking off metrics; it’s about ensuring your model consistently performs in the wild.

Machine Learning 195

Machine Learning 195

Marktechpost

AUGUST 25, 2024

Retrieval-Augmented Generation (RAG) has faced significant challenges in development, including a lack of comprehensive comparisons between algorithms and transparency issues in existing tools. Popular frameworks like LlamaIndex and LangChain have been criticized for excessive encapsulation, while lighter alternatives such as FastRAG and RALLE offer more transparency but lack reproduction of published algorithms.

Algorithm 122

Algorithm NLP Natural Language Processing AI 122

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

Machine Learning Mastery

AUGUST 25, 2024

When we analyze relationships between variables in machine learning, we often find that a straight line doesn’t tell the whole story. That’s where polynomial transformations come in, adding layers to our regression models without complicating the calculation process. By transforming our features into their polynomial counterparts—squares, cubes, and other higher-degree terms—we give linear models the […] The post Capturing Curves: Advanced Modeling with Polynomial R

Machine Learning 94

Machine Learning Data Science 94

Towards AI

AUGUST 25, 2024

Last Updated on September 2, 2024 by Editorial Team Author(s): Souradip Pal Originally published on Towards AI. Let’s deep dive into the math and code it up from scratch This member-only story is on us. Upgrade to access all of Medium. Suppose you’re on the hunt for a new apartment in your dream location — be it Thailand, Japan, or London. You’ve got the money (let’s skip the how for now), but how do you decide on the right price?

Machine Learning 52

Machine Learning AI AI Artificial Intelligence 52

Marktechpost

AUGUST 25, 2024

Creating cutting-edge, interactive applications for the terminal takes a lot of work. Although powerful, terminal-based apps frequently need more sophisticated user interfaces of web or desktop programs. Within the confines of a terminal, developers must create functional and aesthetically pleasing applications. The flexibility and user-friendliness that traditional tools must provide are necessary to construct these complex interfaces swiftly.

Python 105

Python Artificial Intelligence Artificial Intelligence Machine Learning 105

TheSequence

AUGUST 25, 2024

Image Credit: Black Forest Labs Next Week in The Sequence: Edge 425: Our series about SSMs dives into Mamba, the best known SSM model. We review the original Mamba paper by Carnegie Mellon University and Princeton and dive into the GridTape framework for building LLM apps. Edge 426: We discuss Gemma Scope and ShieldGemma, two new tools for interpretability and guardrailing released by Google DeepMind.

Neural Network 52

Neural Network LLM OpenAI AI Researcher 52

Marktechpost

AUGUST 25, 2024

Advanced Machine Learning models called Graph Neural Networks (GNNs) process and analyze graph-structured data. They have proven quite successful in a number of applications, including recommender systems, question-answering, and chemical modeling. Transductive node classification is a typical problem for GNNs, where the goal is to predict the labels of certain nodes in a graph based on the known labels of other nodes.

Neural Network 105

Neural Network Machine Learning ML AI 105

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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.

Marktechpost

AUGUST 25, 2024

The rapid integration of AI technologies in medical education has revealed significant limitations in existing educational tools. Current AI-assisted systems primarily support solitary learning and are unable to replicate the interactive, multidisciplinary, and collaborative nature of real-world medical training. This deficiency poses a significant challenge, as effective medical education requires students to develop proficient question-asking skills, engage in peer discussions, and collaborate

AI 105

AI AI Chatbots Automation 105

Marktechpost

AUGUST 25, 2024

Language models have gained prominence in reinforcement learning from human feedback (RLHF), but current reward modeling approaches face challenges in accurately capturing human preferences. Traditional reward models, trained as simple classifiers, struggle to perform explicit reasoning about response quality, limiting their effectiveness in guiding LLM behavior.

LLM 103

LLM ML AI AI 103

Marktechpost

AUGUST 25, 2024

LinkedIn has recently unveiled its groundbreaking innovation, the Liger (LinkedIn GPU Efficient Runtime) Kernel , a collection of highly efficient Triton kernels designed specifically for large language model (LLM) training. This new technology represents an advancement in machine learning, particularly in training large-scale models that require substantial computational resources.

LLM 124

LLM Large Language Models Machine Learning Artificial Intelligence 124

Marktechpost

AUGUST 25, 2024

Digital marketing has evolved rapidly, and AI technologies have been at the heart of this transformation. Among these, GPT-4, the latest iteration of OpenAI’s Generative Pre-trained Transformer models, spearheads the next wave of innovation. With its sophisticated language capabilities, GPT-4 is revolutionizing content creation, enhancing customer engagement, and optimizing data analysis, thereby reshaping the future of digital marketing.

Data Analysis 119

Data Analysis Chatbots Natural Language Processing Computer Vision 119

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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

Marktechpost

AUGUST 25, 2024

OuteAI has recently made a significant advancement in AI technology with the release of Lite Oute 2 Mamba2Attn 250M. This development marks a pivotal moment for the company and the broader AI community, showcasing the potential of highly efficient, low-resource AI models. The Lite Oute 2 Mamba2Attn 250M is a lightweight model designed to deliver impressive performance while maintaining a minimal computational footprint, addressing the growing demand for scalable AI solutions that can operate eff

Natural Language Processing 111

Natural Language Processing AI Developer AI Development AI Modeling 111