AI News

MAY 15, 2023

We must admit that human intelligence is limited in capacity and ability to process information. That’s essentially what the modern lifecycle of AI/ML products looks like. That requires experience in identifying the problems that can benefit from AI/ML the most, and agile, iterative processes of validating and scaling the ideas.

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Aiiot Talk

AUGUST 10, 2023

Machine learning (ML) and artificial intelligence (AI) have many viable uses in business, including reducing overhead costs. What Are the Benefits of Using ML and AI? Leveraging ML and AI is beneficial because it’s a low-risk, high-reward approach to reducing overhead costs. How Can ML and AI Reduce Overhead Costs?

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Marktechpost

MAY 11, 2024

Information extraction (IE) is a pivotal area of artificial intelligence that transforms unstructured text into structured, actionable data. Despite their expansive capacities, traditional large language models (LLMs) often fail to comprehend and execute the nuanced directives required for precise IE. Check out the Paper.

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Large Language Models Prompt Engineer Prompt Engineering Categorization 105

Unite.AI

JUNE 19, 2023

Adam Asquini is a Director of Information Management & Data Analytics at KPMG in Edmonton. That type of work's also really important and can save organizations a lot of effort and a lot of money in how they do their business, You’re currently the director of information management and data analytics at KPMG.

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Generative AI Responsible AI Artificial Intelligence Artificial Intelligence 244

Towards AI

FEBRUARY 21, 2024

Image generated with DALL-E 3 In the fast-paced world of Machine Learning (ML) research, keeping up with the latest findings is crucial and exciting, but let’s be honest — it’s also a challenge. Enter ML Conference Paper Explorer: your sidekick in navigating the ML paper maze with ease. What’s the next big thing in ML?

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ML Machine Learning AI AI 104

Analytics Vidhya

MAY 17, 2024

Introduction Machine learning (ML) is rapidly transforming various industries. Companies leverage machine learning to analyze data, predict trends, and make informed decisions. Learning ML has become crucial for anyone interested in a data career. From healthcare to finance, its impact is profound.

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Marktechpost

NOVEMBER 21, 2023

It ingeniously applies techniques from natural-language models, akin to ChatGPT, to reconstruct comprehensive information, like oceanic temperatures, from sparse data collected by a limited number of sensors. This ability holds immense value for global climate models, shedding light on crucial information for understanding climate dynamics.

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Convolutional Neural Networks Neural Network Artificial Intelligence Artificial Intelligence 102

Marktechpost

MARCH 11, 2024

This alignment is crucial for information retrieval systems to cater to diverse user search intentions and preferences effectively. Ultimately, INSTRUCTIR is a powerful catalyst, driving advancements in information retrieval systems toward greater user satisfaction and effectiveness in addressing diverse search intents and preferences.

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Machine Learning Large Language Models ML AI 92

Marktechpost

JANUARY 30, 2024

While effective in various applications, the traditional methods face a significant challenge: the integration of semantic and perceptual information, often resulting in inefficiencies and redundancies. It utilizes an autoregressive model based on LLMs for semantic information modeling.

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Large Language Models Machine Learning ML AI 131

Marktechpost

MARCH 26, 2024

Information Retrieval (IR) involves technologies and models that allow users to extract relevant information from large datasets. This field has evolved significantly with modern computational techniques, facilitating more efficient and precise search capabilities across vast digital information landscapes.

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Neural Network Large Language Models ML AI 100

Towards AI

AUGUST 16, 2023

To receive deep insights just like this and more, including top ML papers of the week, job postings, ML tips from real-world experience, and ML stories from researchers and builders, join my newsletter here. This requires a ton of manual labor to read, understand and extract the right information.

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ML AI AI Machine Learning 79

Marktechpost

FEBRUARY 8, 2024

An alternative approach involves indexing text in an information retrieval system and presenting retrieved information to LLMs for current domain-specific knowledge. Join our 36k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup. Fine-tuning downstream tasks further enhances their performance.

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Large Language Models Algorithm ML Artificial Intelligence 134

Chatbots Life

APRIL 27, 2024

For enterprise software, AI and ML are like special effects. By examining how AI and ML in enterprise software can drive business success, we aim to highlight these technologies’ transformational potential and underscore their importance in today’s competitive business environment.

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Marktechpost

JANUARY 12, 2024

One of the most important areas of NLP is information extraction (IE), which takes unstructured text and turns it into structured knowledge. So, instead of extracting structural information from plain text, generative IE approaches that use LLMs to create structural information has recently become very popular.

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Large Language Models Chatbots BERT NLP 129

AWS Machine Learning Blog

NOVEMBER 29, 2023

Data preparation is a crucial step in any machine learning (ML) workflow, yet it often involves tedious and time-consuming tasks. With this integration, SageMaker Canvas provides customers with an end-to-end no-code workspace to prepare data, build and use ML and foundations models to accelerate time from data to business insights.

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Marktechpost

FEBRUARY 8, 2024

With the world of computational science continually evolving, physics-informed neural networks (PINNs) stand out as a groundbreaking approach for tackling forward and inverse problems governed by partial differential equations (PDEs). Join our 36k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup.

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Neural Network Deep Learning AI AI 133

Marktechpost

JANUARY 2, 2024

and Harbin Institute of Technology has introduced KwaiAgents, an information-seeking agent system based on LLMs. Even smaller models, such as 7B or 13B, have demonstrated generalized agent capabilities for tasks involving the retrieval of information from many systems. In recent research, a team of researchers from Kuaishou Inc.

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Large Language Models Natural Language Processing LLM Robotics 99

Mlearning.ai

JULY 30, 2023

THE BASICS Introduction I haven’t had much time to write lately but I feel that there is growing interest in quantum information theory as of lately. On an abstract level, quantum information isn’t that difficult to grasp. In quantum information theory on the other hand those states are presented as | 0 ⟩ and | 1 ⟩.

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Marktechpost

NOVEMBER 28, 2023

Additionally, transcribed text is believed to encapsulate all the necessary semantic information. This was the summary of De-Diffusion, a novel AI technique to convert an input image into a piece of information-rich text that can act as a flexible interface between different modalities, enabling diverse audio-vision-language applications.

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Marktechpost

JANUARY 13, 2024

These documents, often in PDF or image formats, present a complex interplay of text, layout, and visual elements, necessitating innovative approaches for accurate information extraction. The model consistently improved information extraction and question-answering tasks when tested on standard datasets like FUNSD, CORD, and DocVQA.

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AI Researcher AI Research Large Language Models Neural Network 133

Google Research AI blog

APRIL 27, 2023

To best use this data, we need to be able to represent the information present as succinct, informative labels about meaningful diseases and traits, a process called phenotyping. That is where we can use the ability of ML models to pick up on subtle intricate patterns in large amounts of data.

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Marktechpost

SEPTEMBER 6, 2023

GPT3, LaMDA, PALM, BLOOM, and LLaMA are just a few examples of large language models (LLMs) that have demonstrated their ability to store and apply vast amounts of information. Planning for questions that require visual information is a multi-step process due to the complexity of the assignment.

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Marktechpost

FEBRUARY 24, 2024

A significant challenge they face is the production of plausible yet inaccurate responses, a phenomenon often attributed to the models’ inability to consult verified sources of information directly. LLMs typically must catch up when retrieving precise information from specialized fields such as genomics.

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ML @ CMU

MARCH 31, 2023

Our work further motivates novel directions for developing and evaluating tools to support human-ML interactions. Model explanations have been touted as crucial information to facilitate human-ML interactions in many real-world applications where end users make decisions informed by ML predictions.

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Google Research AI blog

APRIL 21, 2023

However, developing and iterating on these ML-based multimedia prototypes can be challenging and costly. However, developing and iterating on these ML-based multimedia prototypes can be challenging and costly. Visual Blocks for ML, formerly called Rapsai, provides a no-code graph building experience through its node-graph editor.

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Machine Learning ML Deep Learning Computer Vision 121

Flipboard

NOVEMBER 26, 2023

Amazon Redshift ML empowers data analysts and database developers to integrate the capabilities of machine learning and artificial intelligence into …

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Large Language Models ML Artificial Intelligence Artificial Intelligence 119

Towards AI

AUGUST 21, 2023

TheSequence is a no-BS (meaning no hype, no news, etc) ML-oriented newsletter that takes 5 minutes to read. One of those areas is visual information-seeking tasks where external knowledge is required to answer a specific question. Throughout the process, a functional memory module retains and preserves information.

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Marktechpost

FEBRUARY 4, 2024

These systems extend the capabilities of LLMs by integrating an Information Retrieval (IR) phase, which allows them to access external data. Interestingly, the balance between relevance and the inclusion of seemingly unrelated information plays a significant role in the system’s overall performance. Check out the Paper.

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Large Language Models Machine Learning Categorization AI 128

Marktechpost

JANUARY 21, 2024

However, applying them to Information Retrieval (IR) tasks remains a challenge due to the scarcity of IR-specific concepts in natural language. Join our 36k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup. Also, don’t forget to follow us on Twitter.

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Large Language Models Natural Language Processing Categorization NLP 140

Marktechpost

JANUARY 20, 2024

The practical deployment of multi-billion parameter neural rankers in real-world systems poses a significant challenge in information retrieval (IR). Join our 36k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup. All credit for this research goes to the researchers of this project.

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BERT Large Language Models LLM AI 131

Marktechpost

NOVEMBER 14, 2023

The ambition of automatically converting informal mathematics into formally provable material is as old as standard mathematics itself. This is challenging because it requires expensive, highly qualified computer science and mathematics specialists to translate informal mathematical knowledge into a formal language manually.

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Large Language Models Neural Network LLM Automation 120

Marktechpost

OCTOBER 20, 2023

Multimodal graph learning can generate descriptive captions for images by combining visual data with textual information. Multimodal graph learning is also used in autonomous vehicles to combine data from various sensors, such as cameras, LiDAR, radar, and GPS, to enhance perception and make informed driving decisions.

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Artificial Intelligence Artificial Intelligence Neural Network Machine Learning 132

Marktechpost

JANUARY 25, 2024

Ypsilanti, USA, have developed a method employing Physics-Informed Neural Networks (PINNs) to deduce complete 3D velocity and pressure fields from 3D temperature snapshots obtained through Tomo-BOS imaging. Join our 36k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup. Michigan Ave.,

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Neural Network Algorithm Machine Learning ML 93

Heartbeat

MARCH 14, 2024

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionary technologies with the potential to transform the field of engineering. The synergy between engineering and AI/ML creates unprecedented opportunities for efficiency, cost reduction, and innovation. Indium Software Why AI and ML in Engineering?

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ML Computer Vision Automation AI 52

Marktechpost

DECEMBER 25, 2023

One of the major issues with CDI, though, is the phase retrieval problem, where the detectors fail to record the phase of the diffracted wave, leading to information loss. The method has numerous applications ranging from nanoscale imaging to X-ray ptychography and astronomical wavefront settings.

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Deep Learning Neural Network AI Researcher AI Research 119

Towards AI

JULY 17, 2023

Pyspark MLlib | Classification using Pyspark ML In the previous sections, we discussed about RDD, Dataframes, and Pyspark concepts. In this article, we will discuss about Pyspark MLlib and Spark ML. Our final DataFrame containing the required information is as below: Let's split the data for training and testing.

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ML Machine Learning Algorithm Categorization 87

Towards AI

MAY 3, 2023

This is where ML CoPilot enters the scene. In this paper, the authors suggest the use of LLMs to make use of past ML experiences to suggest solutions for new ML tasks. Storing past ML insights to guide decision making Machine learning and deep learning models transform unstructured data into numerical vectors called embeddings.

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Large Language Models ML Machine Learning LLM 81