AI Impacts

OCTOBER 18, 2023

Some are papers, some are blog posts, some are shared google docs. Thanks for reading AI Impacts blog! The sources are not all of the same type. The type signature of the claims made in the sources varies. Subscribe for free to receive new posts and support my work.

Deep Learning 147

Deep Learning AI AI 147

IBM Journey to AI blog

MAY 13, 2024

This blog series demystifies enterprise generative AI (gen AI) for business and technology leaders. In the previous blog , we discussed the differentiated approach by IBM to delivering enterprise-grade models. It provides simple frameworks and guiding principles for your transformative artificial intelligence (AI) journey.

Generative AI 177

Generative AI AI AI Prompt Engineer 177

Shreyansh Singh

MAY 28, 2023

Paper : Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training Link : [link] Authors : Hong Liu, Zhiyuan Li, David Hall, Percy Liang, Tengyu Ma Code : [link] I have also released an annotated version of the paper. If you are interested, you can find it here. Hopefully it helps someone! How does it work?

Deep Learning 52

Deep Learning LLM 52

Unite.AI

MARCH 15, 2024

AI Summaries: Provides AI generated summaries with images and videos for insights. Categorical Searches: Users can search within categories such as tweets, papers, or blogs for more targeted and effective searching. Features Ad-Free: Providing a clean, ad-free reading experience.

AI 306

AI AI OpenAI LLM 306

Shreyansh Singh

MAY 2, 2021

Paper : Improving Language Understanding by Generative Pre-Training Link : [link] Blog : [link] Authors : Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever Code : [link] What? The paper assumes access to a large corpus of unlabeled text and several datasets with manually annotated training examples (the target tasks).

Deep Learning 52

Deep Learning Explainability 52

Ehud Reiter

MARCH 25, 2024

Anyways, a few weeks ago we had a workshop where computer scientists, clinicians, patients, and other interested parties discussed related topics, including some work of one of my students, Mengzuan Sun, is doing on using chatGPT (GPT4) to explain complex medical notes to patients ( blog ). ChatGPT made some mistakes in the summaries.

Explainability 124

Explainability ChatGPT Computer Scientist NLP 124

AssemblyAI

SEPTEMBER 13, 2023

AI summarization models automatically distill text or transcripts, like from a document, sales call, podcast, or research paper, into its most important parts. This method does not alter the original language used in the text, instead compiling the summary from the original language of the text. What is AI summarization? Fireflies.ai

Auto-complete 130

Auto-complete AI AI Automation 130

Ehud Reiter

NOVEMBER 12, 2023

Of course commercial NLP companies have zillions of white papers and case studies which claim to demonstrate real-world impact, but these are marketing documents, not scientific experiments. Anyways, I think we need at least some evaluations that scientifically measure real-world impact!

NLP 117

NLP ML AI AI 117

Towards AI

SEPTEMBER 10, 2023

Learn to harness AI technology to distill hours of content into concise summaries, saving you time and enhancing your understanding. Unless you’re armed with a pen and paper or diligently… Read the full blog for free on Medium. Discover how ChatGPT can transform your podcast-listening experience.

ChatGPT 113

ChatGPT AI AI Data Science 113

Towards AI

AUGUST 28, 2023

Image by author I have read dozens of machine learning papers and am starting to get the hang of how to approach studying a paper.This first involves understanding what the goal of reading a specific paper is! Now, before you get to skimming the new paper, you first need to know about what the newest and hottest publication is.

Machine Learning 95

Machine Learning Computer Vision Large Language Models Explainability 95

Ehud Reiter

FEBRUARY 13, 2023

A reader of my blog contacted me and asked me whether people would accept some errors in chatGPT texts. I should add that nothing I say below is novel, so people who are familiar with this topic may not learn much from this blog. Example: Consultation Summaries Let me start with an example from medicine.

ChatGPT 100

ChatGPT Explainability Chatbots 100

Topbots

MAY 17, 2023

In 2015, a research paper from Stanford University and UC Berkeley introduced diffusion models, coming originally from statistical physics, into the field of machine learning. We’ll start our overview with this paper and then we’ll see what other influential research papers have revolutionized the field of image generation.

Neural Network 97

Neural Network Computer Vision OpenAI Machine Learning 97

Towards AI

FEBRUARY 2, 2024

Image Source: Hugging Face blog When you have a specific idea in mind, say summarizing an article, a small specialist model that is designed for that specific task can perform just as well as a general-purpose Large Language model. Last Updated on February 2, 2024 by Editorial Team Author(s): Saqib Jan Originally published on Towards AI.

Generative AI 101

Generative AI Machine Learning AI AI 101

BAIR

OCTOBER 16, 2023

Background Figure 2: A description of the three stages of RLHF from an OpenAI blog post. You can find more details in our original paper. In summarization, we utilize the TL;DR dataset where the prompt (x) is a forum post from Reddit, and (y) is a corresponding summary. BibTex This blog is based on our recent paper and blog.

Algorithm 225

Algorithm Large Language Models LLM OpenAI 225

Flipboard

DECEMBER 6, 2023

In a world full of data, summarizing long texts into brief summaries saves time and helps make informed decisions. Extractive summarization Extractive summarization is a technique used in NLP and text analysis to create a summary by extracting key sentences. In this post, we focus on the BERT extractive summarizer.

BERT 128

BERT Large Language Models Artificial Intelligence Artificial Intelligence 128

Topbots

APRIL 11, 2023

BERT by Google Summary In 2018, the Google AI team introduced a new cutting-edge model for Natural Language Processing (NLP) – BERT , or B idirectional E ncoder R epresentations from T ransformers. GPT-3 by OpenAI Summary The OpenAI team introduced GPT-3 as an alternative to having a labeled dataset for every new language task.

NLP 98

NLP Large Language Models BERT Natural Language Processing 98

AssemblyAI

AUGUST 22, 2023

In particular, the original GPT paper demonstrated the effectiveness of textual pretraining. The same pretrained model can be finetuned for different downstream tasks One year later in 2019, the GPT-2 paper was released. The GPT-2 paper investigated how the model improved as a function of this scaling process.

LLM 242

LLM ChatGPT AI Modeling Chatbots 242

Marktechpost

JANUARY 17, 2024

These datasets include medical question-answering with multiple-choice questions, medical reasoning with long-form questions vetted by experts, summaries of notes from electronic health records (EHRs), and interactions from large-scale recorded medical conversations. Check out the Paper and Blog.

Large Language Models 112

Large Language Models LLM Artificial Intelligence Artificial Intelligence 112

Unite.AI

AUGUST 20, 2023

Copy AI doesn't just write short-form content like social media posts or product descriptions; it also writes long-form articles and blog posts 10x faster using its powerful content generator. By the end of this blog, you will clearly understand whether Copy.ai Use Copy AI to generate ideas for blog posts and articles.

AI 246

AI AI Natural Language Processing Explainability 246

TheSequence

DECEMBER 3, 2023

We review the original RLAIF paper and NVIDIA’s NeMo framework. In summary, re:Invent showcased AWS's strength in the generative AI sector. GNoME Google DeepMind published a paper detailing Graph Networks for Materials Exploration (GNoME), a deep learning model that was able to discover new materials.

AI Strategy 110

AI Strategy Generative AI DevOps Data Quality 110

AI Impacts

APRIL 15, 2024

There are no constraints on the format — we will accept essays, blog posts, papers 2 , websites, or other written artefacts 3 of any length. As part of your submission you will be asked to provide a summary of 100–200 words. 2 We recognise that the timeline may be on the tight side for thoroughly researched papers.

Automation 124

Automation AI AI 124

Towards AI

JULY 21, 2023

For a Summary/Timeline: Uncovering Cicada Wiki NEW USERS, PLEASE READ THIS FAQ IF YOU DON'T KNOW WHAT PGP IS CLICK HERE uncovering-cicada.fandom.com Visit Nox’s YouTube channel if you are interested in understanding how they cracked previous Cicada puzzles ante-Liber Primus. The script works for the GLUE datasets.

NLP 81

NLP Inference Engine Natural Language Processing Chatbots 81

IBM Journey to AI blog

NOVEMBER 29, 2023

In this paper, we showcase how to easily deploy a banking application on both IBM Cloud for Financial Services and Satellite , using automated CI/CD/CC pipelines in a common and consistent manner. Details of each docker image is stored in an inventory repository, which is explained in detail in the Continuous Deployment section of this blog.

DevOps 228

DevOps Automation Explainability 228

Google Research AI blog

MAY 12, 2023

The task output is the desired outcome for the target tasks, e.g., a screen summary or an answer to a user question. They can generate more accurate summaries than the Screen2Words benchmark model that we previously introduced using UI-specific text, as highlighted in the colored text and boxes below.

LLM 104

LLM Large Language Models Natural Language Processing Algorithm 104

Allen AI

OCTOBER 30, 2023

New Intelligent Reading Interfaces Research and The Semantic Reader Open Research Platform This year at the 36th Annual ACM UIST Conference, researchers from AI2 will present papers on two new AI-powered intelligent reading interfaces for scholarly documents —  Papeo and Synergi. Zhang,* Joseph Chee Chang.*

Natural Language Processing 52

Natural Language Processing NLP Large Language Models AI 52

Allen AI

NOVEMBER 27, 2023

For a more detailed description of our methodology and results, please refer to our paper —  SciRepEval: A Multi-Format Benchmark for Scientific Document Representations which has been accepted to appear in EMNLP 2023. For each of these models, the input paper text is represented by a combination of its title and abstract.

BERT 98

BERT AI AI 98

BAIR

APRIL 6, 2023

IFL Formalism and Algorithms To this end, in a recent paper at the Conference on Robot Learning we introduced the paradigm of Interactive Fleet Learning (IFL) , the first formalism in the literature for interactive learning with multiple robots and multiple humans. See the paper for more of the mathematical details.

Robotics 246

Robotics Algorithm Continuous Learning Artificial Intelligence 246

Unite.AI

JUNE 15, 2023

This may involve attending conferences, reading research papers, or participating in industry forums. Regularly reading research papers, following industry blogs, and participating in online forums can help NLP Engineers stay informed.

Natural Language Processing 245

Natural Language Processing NLP Machine Learning Algorithm 245

Pragnakalp

APRIL 29, 2024

In our blog, we are specifically focusing on leveraging Microsoft’s Phi-3 model as the Language Model for the RAG framework. In this blog, we’ll be using the “ Phi-3-mini-4k-instruct ” model from the family of Phi models, which you can find on Hugging Face. Q3: What are the 2 main focuses of the paper?

Deep Learning 59

Deep Learning Big Data LLM Data Science 59

Topbots

JULY 6, 2023

GPT-3 by OpenAI Summary The OpenAI team introduced GPT-3 as an alternative to having a labeled dataset for every new language task. Research paper: Language Models are Few-Shot Learners Where can you get implementation code? The Most Important Large Language Models (LLMs) and Visual Language Models (VLMs) in 2023 1.

LLM 52

LLM Large Language Models Natural Language Processing OpenAI 52

ML @ CMU

MARCH 31, 2023

This blog post discusses the effectiveness of black-box model explanations in aiding end users to make decisions. We observe that explanations do not in fact help with concrete applications such as fraud detection and paper matching for peer review. Peer review paper matching is an example of a document matching application.

ML 98

ML Explainability Algorithm Machine Learning 98

IBM Journey to AI blog

MARCH 20, 2024

In the rest of this paper, we will explore how Cloud Pak for Integration, deployed on Red Hat OpenShift is the best way to provide integrations deploying in AWS. Perhaps you need to discover what’s happening in your business and respond quickly to events. What is ROSA? And your business can focus on the future rather than the past.

Automation 154

Automation DevOps AI AI 154

Allen AI

DECEMBER 12, 2023

Today, alongside a new paper describing these results, which won “best paper” at the 2023 NeurIPS Computational Sustainability meeting, we are releasing the model architectures, data annotations, and code, all under permissive open-source licenses (Apache 2.0). More details can be found in the paper.

Computer Vision 98

Computer Vision Data Drift AI AI 98

Heartbeat

MAY 3, 2023

A large document’s content can be rapidly understood using this tool and can also be used to summarize news stories or academic papers. Pick the Best Sentences To make a summary of the text, we can choose the top n sentences with the highest scores. The ultimate summary is made by combining these sentences.

Deep Learning 52

Deep Learning Natural Language Processing Python Data Scientist 52

Allen AI

AUGUST 18, 2023

A more comprehensive paper is in the works. For Dolma, we leverage Semantic Scholar’s corpus by including papers from peS2o , a subset of 38M permissibly licensed scientific manuscripts. The following table presents a high-level summary of language models that don’t make their pretraining data available. Question marks ( ?

Auto-complete 98

Auto-complete Large Language Models NLP Explainability 98

BAIR

OCTOBER 16, 2023

Background Figure 2: A description of the three stages of RLHF from an OpenAI blog post. You can find more details in our original paper. In summarization, we utilize the TL;DR dataset where the prompt (x) is a forum post from Reddit, and (y) is a corresponding summary. BibTex This blog is based on our recent paper and blog.

Algorithm 100

Algorithm Large Language Models LLM OpenAI 100

deepsense.ai

NOVEMBER 30, 2023

In this blog post, we will focus on the widely-discussed Llama 2 model. Interestingly, there is also a model with 34 billion parameters, but according to Meta’s research paper, it has not been released to the public due to a lack of time to ensure the self-imposed safety threshold. It is also optimized to run locally on Windows.

Artificial Intelligence 99

Artificial Intelligence Artificial Intelligence AI AI 99