IBM Journey to AI blog

AUGUST 12, 2024

It helps companies streamline and automate the end-to-end ML lifecycle, which includes data collection, model creation (built on data sources from the software development lifecycle), model deployment, model orchestration, health monitoring and data governance processes.

Big Data 266

Big Data DevOps Automation Machine Learning 266

Heartbeat

FEBRUARY 29, 2024

After closely observing the software engineering landscape for 23 years and engaging in recent conversations with colleagues, I can’t help but feel that a specialized Large Language Model (LLM) is poised to power the following programming language revolution.

Software Engineer 52

Software Engineer Software Development Large Language Models LLM 52

Marktechpost

SEPTEMBER 11, 2024

Both models were trained using IBM’s Power scheduler and exhibit state-of-the-art performance across various natural language processing tasks. Conclusion IBM’s release of PowerLM-3B and PowerMoE-3B marks a pivotal advancement in LLMs and NLP. trillion tokens.

Natural Language Processing 120

Natural Language Processing Large Language Models Neural Network Software Engineer 120

Unite.AI

JULY 1, 2024

Rob has over 20 years of experience in software engineering, product management, operations, and the development of leading-edge artificial intelligence and web-scale technologies. In the same way software engineers and QA can scan, test and validate their code, we provide the same capabilities for AI models.

Explainability 173

Explainability Software Engineer AI Modeling Responsible AI 173

Flipboard

FEBRUARY 10, 2025

He is currently focused on combining his background in software engineering, DevOps, and machine learning to help customers deliver machine learning workflows at scale. Bobby Lindsey is a Machine Learning Specialist at Amazon Web Services. Hes been in technology for over a decade, spanning various technologies and multiple roles.

LLM 161

LLM AI AI Python 161

Flipboard

SEPTEMBER 25, 2023

We borrow proven techniques from the latest in NLP (natural language processing) academia to build evaluation tooling that any software engineer can use. Devs shouldn’t be neck-deep in evaluation pipelines just to test their software, so we solve that complexity for them.

Large Language Models 169

Large Language Models Explainability Natural Language Processing Software Engineer 169

ODSC - Open Data Science

SEPTEMBER 19, 2023

Prompt engineers take on this challenge by optimizing LLMs to process and generate content at scale. This task involves a combination of software engineering expertise and computational efficiency. Engineers delve into the architecture of LLMs, identifying potential bottlenecks and areas for improvement.

Prompt Engineer 98

Prompt Engineer Prompt Engineering Large Language Models Software Engineer 98

AWS Machine Learning Blog

JANUARY 31, 2024

Embeddings play a key role in natural language processing (NLP) and machine learning (ML). Text embedding refers to the process of transforming text into numerical representations that reside in a high-dimensional vector space. Why do we need an embeddings model? Nitin Eusebius is a Sr.

Natural Language Processing 129

Natural Language Processing Machine Learning Computer Vision ML 129

AWS Machine Learning Blog

MARCH 22, 2024

He partners with software companies to architect and implement cloud-based solutions on AWS. Before joining AWS, he worked for AWS customers and partners in software engineering, consulting, and architecture roles for 8+ years. Matt Middleton is the Senior Product Partner Ecosystem Manager at Contentful.

Large Language Models 108

Large Language Models Natural Language Processing NLP Software Engineer 108

AWS Machine Learning Blog

MARCH 4, 2024

However, when employing the use of traditional natural language processing (NLP) models, they found that these solutions struggled to fully understand the nuanced feedback found in open-ended survey responses. The following table compares training a traditional NLP model vs. in-context training of an LLM.

NLP 119

NLP Prompt Engineer Prompt Engineering LLM 119

ODSC - Open Data Science

MARCH 28, 2023

Machine Learning for Finance Focused on the tools and skills that are becoming increasingly essential in the finance industry, this track will help you identify and grow the software engineering skills you need to excel as a data scientist in finance.

Data Science 92

Data Science Deep Learning Machine Learning Neural Network 92

ODSC - Open Data Science

MAY 22, 2023

Introduction to Data Analysis Using Pandas Stefanie Molin | Software Engineer, Data Scientist, Chief Information Security Office | Bloomberg LP | Author of Hands-On Data Analysis with Pandas This session will equip you with the knowledge you need to effectively use pandas to make working with data easier.

Data Science 97

Data Science Python Machine Learning Data Analysis 97

Towards AI

JANUARY 6, 2025

Artificial Intelligence graduate certificate by STANFORD SCHOOL OF ENGINEERING Artificial Intelligence graduate certificate; taught by Andrew Ng, and other eminent AI prodigies; is a popular course that dives deep into the principles and methodologies of AI and related fields.

Artificial Intelligence 105

Artificial Intelligence Artificial Intelligence Computer Vision Deep Learning 105

AWS Machine Learning Blog

JANUARY 4, 2024

One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. Instead of dealing with complex technical code, business users and data analysts can ask questions related to data and insights in plain language.

Prompt Engineer 136

Prompt Engineer Prompt Engineering Generative AI LLM 136

ODSC - Open Data Science

DECEMBER 19, 2023

Machine learning engineers use their knowledge of machine learning algorithms, programming languages, and data science tools to build models that can be used to automate tasks and make predictions. They work closely with data scientists, software engineers, and business analysts to ensure that the models are accurate and effective.

AI Product Manager 96

AI Product Manager AI Product Management Prompt Engineer Prompt Engineering 96

Towards AI

AUGUST 16, 2023

In fact, AI/ML graduate textbooks do not provide a clear and consistent description of the AI software engineering process. Therefore, I thought it would be helpful to give a complete description of the AI engineering process or AI Process, which is described in most AI/ML textbooks [5][6].

Software Engineer 98

Software Engineer Machine Learning Artificial Intelligence Artificial Intelligence 98

AWS Machine Learning Blog

MARCH 13, 2025

Pranav specializes in multimodal architectures, with deep expertise in computer vision (CV) and natural language processing (NLP). Previously, he worked in the semiconductor industry, developing AI/ML models to optimize semiconductor processes using state-of-the-art techniques.

LLM 83

LLM Machine Learning AI AI 83

The MLOps Blog

FEBRUARY 15, 2024

Due to the rise of LLMs and the shift towards pre-trained models and prompt engineering, specialists in traditional NLP approaches are particularly at risk. Data scientists and NLP specialists can move towards analytical roles or into engineering to stay relevant. Who are the people most at risk of being laid off?

NLP 59

NLP Natural Language Processing Data Scientist Software Engineer 59

Google Research AI blog

MARCH 27, 2023

Posted by Rahul Goel and Aditya Gupta, Software Engineers, Google Assistant Virtual assistants are increasingly integrated into our daily routines. As we use these assistants, we are also becoming more accustomed to using natural language to accomplish tasks that we once did by hand.

NLP 98

NLP Natural Language Processing Software Engineer Data Quality 98

AWS Machine Learning Blog

NOVEMBER 1, 2023

In this post, Reveal experts showcase how they used Amazon Comprehend in their document processing pipeline to detect and redact individual pieces of PII. Amazon Comprehend is a fully managed and continuously trained natural language processing (NLP) service that can extract insight about the content of a document or text.

Software Engineer 107

Software Engineer Metadata Machine Learning NLP 107

Explosion

JUNE 18, 2021

We’ve been running Explosion for about five years now, which has given us a lot of insights into what Natural Language Processing looks like in industry contexts. In this blog post, I’m going to discuss some of the biggest challenges for applied NLP and translating business problems into machine learning solutions.

NLP 52

NLP Machine Learning Natural Language Processing DevOps 52

AWS Machine Learning Blog

DECEMBER 29, 2022

He specializes in Natural Language Processing (NLP), Large Language Models (LLM) and Machine Learning infrastructure and operations projects (MLOps). Aditi Rajnish is a Second-year software engineering student at University of Waterloo.

Machine Learning 122

Machine Learning Natural Language Processing Data Scientist Data Analysis 122

AWS Machine Learning Blog

JULY 24, 2024

Einstein has a list of over 60 features, unlocked at different price points and segmented into four main categories: machine learning (ML), natural language processing (NLP), computer vision, and automatic speech recognition. These models are designed to provide advanced NLP capabilities for various business applications.

LLM 122

LLM Machine Learning Auto-complete NLP 122

Chatbots Life

MAY 12, 2023

As everything is explained from scratch but extensively I hope you will find it interesting whether you are NLP Expert or just want to know what all the fuss is about. We will discuss how models such as ChatGPT will affect the work of software engineers and ML engineers. Will ChatGPT replace software engineers?

ChatGPT 90

ChatGPT Software Engineer NLP ML Engineer 90

ODSC - Open Data Science

JULY 22, 2024

Be sure to check out her talk, “ Retrieval-Augmented Generation (RAG): A Synergistic Approach to Natural Language Understanding and Generation ,” there! In summary, Retrieval-Augmented Generation (RAG) offers a powerful and innovative solution to some of the most significant challenges in Natural Language Processing.

Natural Language Processing 52

Natural Language Processing NLP Data Science Software Engineer 52

AWS Machine Learning Blog

MARCH 10, 2025

Amazon Bedrock Guardrails implements content filtering and safety checks as part of the query processing pipeline. Anthropic Claude LLM performs the natural language processing, generating responses that are then returned to the web application.

DevOps 92

DevOps Metadata Auto-complete Automation 92

AWS Machine Learning Blog

AUGUST 14, 2023

In this post and accompanying notebook, we demonstrate how to deploy the BloomZ 176B foundation model using the SageMaker Python simplified SDK in Amazon SageMaker JumpStart as an endpoint and use it for various natural language processing (NLP) tasks.

NLP 82

NLP Prompt Engineer Prompt Engineering Robotics 82

AWS Machine Learning Blog

MARCH 13, 2025

The emergence of generative AI agents in recent years has contributed to the transformation of the AI landscape, driven by advances in large language models (LLMs) and natural language processing (NLP).

AI 88

AI AI Automation LLM 88

Towards AI

MAY 20, 2023

Developing custom LLMs also necessitates a team with expertise in machine learning, natural language processing (NLP), and software engineering, which can be challenging to find and retain, adding to the complexity and cost of the process.

LLM 98

LLM Large Language Models Chatbots Natural Language Processing 98

Google Research AI blog

FEBRUARY 1, 2023

Posted by Shayne Longpre, Student Researcher, and Adam Roberts, Senior Staff Software Engineer, Google Research, Brain Team Language models are now capable of performing many new natural language processing (NLP) tasks by reading instructions, often that they hadn’t seen before.

NLP 89

NLP Natural Language Processing Software Engineer Machine Learning 89

Sebastian Ruder

JANUARY 24, 2022

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP). If CNNs are pre-trained the same way as transformer models, they achieve competitive performance on many NLP tasks [28]. Credit for the title image: Liu et al. Why is it important?   What happened?  

NLP 52

NLP ML BERT Computational Linguistics 52

Marktechpost

JULY 5, 2024

These courses cover foundational topics such as machine learning algorithms, deep learning architectures, natural language processing (NLP), computer vision, reinforcement learning, and AI ethics. Udacity offers comprehensive courses on AI designed to equip learners with essential skills in artificial intelligence.

Data Science 60

Data Science Machine Learning Data Analysis Software Engineer 60

AWS Machine Learning Blog

MAY 10, 2023

We cover computer vision (CV), natural language processing (NLP), classification, and ranking scenarios for models and ml.c6g, ml.c7g, ml.c5, and ml.c6i SageMaker instances for benchmarking. 4xlarge; for the PyTorch NLP models, the cost savings is about 30–50% compared to c5 and c6i.4xlarge 4xlarge instances.

Machine Learning 90

Machine Learning Software Development Deep Learning ML 90

Ines Montani

DECEMBER 13, 2024

I also got to travel a lot and met many cool people, and its been incredibly motivating to see that our vision for applied NLP resonates so much with the developer community. View all talks Calendar Interviews and discussions Ines Montani on Natural Language Processing (Software Engineering Radio) AI The Artistic Intelligence?

NLP 52

NLP Software Engineer Natural Language Processing Large Language Models 52

AWS Machine Learning Blog

FEBRUARY 21, 2025

His area of research is all things natural language (like NLP, NLU, and NLG). His research publications are on natural language processing, personalization, and reinforcement learning. As a business process management expert, he participated in BPO projects for more than 7 years.

LLM 79

LLM AI AI Data Scientist 79

AWS Machine Learning Blog

NOVEMBER 27, 2023

The task parameter is used to define the natural language processing (NLP) task. Currently, he is focused on developing strategies for fine-tuning and optimizing the inference performance of Large Language Models. Harish Tummalacherla is Software Engineer with Deep Learning Performance team at SageMaker.

LLM 110

LLM Deep Learning Large Language Models Machine Learning 110

ODSC - Open Data Science

JANUARY 25, 2023

To improve the speed of your development cycle and the accuracy of your ML models, Azure ML is now offering the opportunity to leverage the power of automated ML for specific key scenarios, such as vision and natural language processing (NLP) models.

Machine Learning 59

Machine Learning Data Scientist Python ML 59