Marktechpost

MAY 26, 2024

Machine translation (MT) has made impressive progress in recent years, driven by breakthroughs in deep learning and neural networks. However, the challenge of literary translations for MT systems is difficult to solve. Literary texts, known for their complex language, figurative expressions, cultural variations, and unique feature styles, create problems that are hard for machines to overcome Due to this complexity, literary translation becomes one of the most challenging areas within machine t

Large Language Models 138

Large Language Models Neural Network LLM Deep Learning 138

TheSequence

MAY 26, 2024

Created Using DALL-E Next Week in The Sequence: Edge 399: Our series about autonomous agents continues with an overview of external aid planning. We dive into IBM’s Simplan method for planning in LLMs and review the Langroid framework for autonomous agents. Edge 340: A must read about AlphaFold 3 which expanded capabilities to predict many of the life’s molecules.

Generative AI 105

Generative AI LLM AI AI 105

Marktechpost

MAY 26, 2024

The rapid growth of AI and complex neural networks drives the need for efficient hardware that suits power and resource constraints. In-memory computing (IMC) is a promising solution for developing various IMC devices and architectures. Designing and deploying these systems requires a comprehensive hardware-software co-design toolchain that optimizes across devices, circuits, and algorithms.

Neural Network 131

Neural Network Convolutional Neural Networks Deep Learning Automation 131

Robot Writers AI

MAY 26, 2024

The Top 100 (Mostly AI-Powered) Changes Promised by Google While Google has been throwing a blizzard-of-bucks at AI for a while now, it can be tough for writers to distill how all that green will make their lives easier. This piece on Google’s blog has all the answers. It cuts through all the noise and hype and offers a succinct, just-the-facts-ma’am rundown on all the upgrades (mostly AI-driven) Google is promising to roll-out in coming months.

Chatbots 52

Chatbots Robotics AI Chatbots ChatGPT 52

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

Marktechpost

MAY 26, 2024

The popularity of AI is soaring, with businesses across industries harnessing its innovation potential. AWS is pivotal in this trend, offering robust AI solutions and services. AWS courses on AI topics provide invaluable knowledge and skills, empowering individuals to leverage AI effectively enabling them to stay ahead in today’s competitive landscape.

Data Scientist 128

Data Scientist Prompt Engineer Prompt Engineering Machine Learning 128

Marktechpost

MAY 26, 2024

Soon after OpenAI’s success with ChatGPT, Google launched one of its own multimodel large language models (MLLM). Google envisioned a greater future with Gemini (then known as Bard) from the start; hence, they made Gemini a multimodel from the beginning and stayed true to their vision. If not the best, Google Gemini might be the most complete large language model (LLM), and we haven’t even scraped the surface of the Gemini Advanced.

Data Analysis 118

Data Analysis Large Language Models LLM ChatGPT 118

Marktechpost

MAY 26, 2024

Anthropic AI’s Claude family of models represents a great challenging feat for GPT models in AI technology. With the release of the Claude 3 series, Anthropic has expanded its models’ capabilities and performance, catering to various applications from text generation to advanced vision processing. Let’s have an overview of these developments, highlighting the advancements and comparative features of the models within the Claude family.

Metadata 114

Metadata AI AI Large Language Models 114

Marktechpost

MAY 26, 2024

Anomaly detection in time series data is a crucial task with applications in various domains, from monitoring industrial systems to detecting fraudulent activities. The intricacies of time series anomalies, including early or delayed detections and varying anomaly durations, are not well captured by conventional metrics like Precision and Recall, intended for independent and identically distributed (iid) data.

Categorization 109

Categorization Algorithm ML Artificial Intelligence 109

Marktechpost

MAY 26, 2024

Google Cloud AI Researchers have introduced LANISTR to address the challenges of effectively and efficiently handling unstructured and structured data within a framework. In machine learning, handling multimodal data—comprising language, images, and structured data—is increasingly crucial. The key challenge is the issue of missing modalities in large-scale, unlabeled, and structured data like tables and time series.

Machine Learning 108

Machine Learning AI AI AI Research 108

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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

MAY 26, 2024

LLMs demonstrate emergent intelligence with increased parameters, computes, and data, hinting at artificial general intelligence. Despite advancements, deployed LLMs still exhibit errors like hallucinations, bias, and factual inaccuracies. Also, the constant evolution of knowledge challenges their pretraining. Addressing errors promptly during deployment is crucial, as retraining or finetuning is often prohibitively costly, posing sustainability issues for accommodating lifelong knowledge growth

LLM 106

LLM ML Large Language Models Artificial Intelligence 106

Marktechpost

MAY 26, 2024

Data structures and algorithms are crucial for efficient problem-solving in computer science, enabling effective data organization and manipulation for fast, reliable software. Learning them enhances your coding skills and prepares you for technical interviews and real-world challenges. This article lists the top data structure and algorithms courses to help you excel in software development and interviews.

Algorithm 103

Algorithm Software Development Data Science Artificial Intelligence 103

Marktechpost

MAY 26, 2024

Local image feature matching techniques help identify fine-grained visual similarities between two images. Although there is a lot of progress in this area, these advancements don’t account for the generalization capability of image-matching models. Many models that focus on specific visual domains with lots of training data, show lower performance on out-of-domain data compared to traditional methods in some cases.

Deep Learning 99

Deep Learning ML Computer Vision Artificial Intelligence 99

Marktechpost

MAY 26, 2024

Financial analysis has always been crucial for interpreting market trends, predicting economic outcomes, and providing investment strategies. This field, traditionally rooted in data, has increasingly turned to artificial intelligence (AI) and algorithmic methods to handle the vast and complex data generated daily. AI’s role in finance has grown significantly, automating tasks once performed by human analysts and enhancing the accuracy and efficiency of financial analysis.

LLM 132

LLM Large Language Models AI AI 132

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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