AI Weekly

JUNE 6, 2024

Hear Pitney Bowes experts David Bildeau and Justin Laurenzi explain how to develop a shipping strategy that’s “just right” for your growing business, so you can ship happily ever after. short for “private investigator”) – operates within Amazon fulfilment centres across North America, where it will scan millions of products daily for defects.

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IBM Journey to AI blog

AUGUST 2, 2024

Depending on which role you have as a company, you will need to comply with different requirements,” Simons explains. The EU already enacted a comprehensive data privacy and security law in 2018 with the GDPR. . “The AI Act defines different rules and definitions for deployers, providers, importers.

Categorization 124

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Unite.AI

SEPTEMBER 29, 2023

In 2018, my friend Alex and I started Progressify, a mobile-first e-commerce storefront. Elai allows you to generate any type of video content, ranging from L&D videos to product explainers and personalized sales videos at scale via API. For lipsync and video rendering, we use our own in-house models.

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Generative AI ML Explainability Machine Learning 269

Unite.AI

JANUARY 13, 2024

Yolov8 Explained YOLO (You Only Live Once) is a popular computer vision model capable of detecting and segmenting objects in images. Yolov3: Launched in 2018, Yolov3 presented new features such as a more effective backbone network, multiple anchors, and spatial pyramid pooling for multi-scale feature extraction.

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NVIDIA

DECEMBER 4, 2023

Three technical reasons, and many stories, explain why that’s so. Since its 2018 launch, MLPerf , the industry-standard benchmark for AI, has provided numbers that detail the leading performance of NVIDIA GPUs on both AI training and inference. That’s up from less than 100 million parameters for a popular LLM in 2018.

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Unite.AI

OCTOBER 8, 2024

It was 2018, and AI didn’t generate as much attention then as it does now, but our team worked hard to create items for images and videos using AI that didn’t exist then. Can you explain how HeyGen achieves this and maintains natural lip sync and voice quality? Later on, I switched teams to work on the AI-augmented camera.

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Marktechpost

NOVEMBER 23, 2023

Transformation Lab in 2018 and most recently (together with Real AI) is founding member of Europe’s first Human Centered AI Masters. The company incubates projects to revolutionize industry verticals with transformative, explainable, and impactful AI, having conducted EU-funded projects in Healthcare, Ethics, and Energy.

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Large Language Models LLM AI AI 126

IBM Journey to AI blog

SEPTEMBER 23, 2024

“The ISS only covers an area up to 55 degrees North and 55 degrees South within its flight path,” explained Müller. The original version of ICARUS was groundbreaking but limited.

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Explainability 113

Marktechpost

JUNE 9, 2024

Explainable AI (xAI) methods, such as saliency maps and attention mechanisms, attempt to clarify these models by highlighting key ECG features. The study utilized four extensive 12-lead ECG databases: PTB-XL, Georgia-12-Lead, China Physiological Signal Challenge 2018 (CPSC2018), and Chapman-Shaoxing, all sampled at 500 Hz.

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Dlabs.ai

JULY 19, 2023

The International Data Corporation predicts that the global datasphere will swell from 33 zettabytes in 2018 to a staggering 175 zettabytes by 2025. Possible solution: Explainable AI Fortunately, a promising solution exists in the form of Explainable AI.

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Pickl AI

APRIL 8, 2024

Example In 2018, a self-driving car developed by Uber struck and killed a pedestrian in Arizona. Example In 2018, it was revealed that Cambridge Analytica, a political consulting firm, had improperly harvested the personal data of millions of Facebook users without their consent. How Can We Ensure the Transparency of AI Systems?

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Unite.AI

OCTOBER 30, 2024

In my last year at Amazon, in 2018,I worked on a project we referred to as the “Star Trek computer,” inspired by the famous sci-fi franchise. Can you explain how your AI understands deeper customer intent and the benefits this brings to customer service? Level AI's NLU technology goes beyond basic keyword matching.

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AI Impacts

FEBRUARY 1, 2023

But this model, on its own, is inadequate for AI, for reasons I will explain in the next section. 5 I will not explain this problem in detail, but I will list some aspects of it here, along with real-world examples, and you can read more about it elsewhere. arXiv preprint arXiv:1803.03453 (2018). ” Cimpanu C.

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Marktechpost

DECEMBER 18, 2023

In a study conducted in 2018, MIT researchers demonstrated that the internal representations generated by these models exhibited similarities to the neural patterns observed in functional magnetic resonance imaging (fMRI) scans of individuals listening to the same sounds.

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Neural Network Explainability AI Research AI Researcher 97

Unite.AI

JULY 12, 2024

Acquired by Google in 2018, Socratic has become a go-to study companion for students looking for quick, reliable answers and in-depth explanations across a wide range of subjects, including math, science, literature, and social studies.

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IBM Journey to AI blog

AUGUST 1, 2023

An open-source model, Google created BERT in 2018. studio for new foundation models, generative AI and machine learning The watsonx.data fit-for-purpose data store, built on an open lakehouse architecture The watsonx.governance toolkit, to accelerate AI workflows that are built with responsibility, transparency and explainability.

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Generative AI BERT Data Scientist Machine Learning 189

Towards AI

APRIL 7, 2024

This article seeks to also explain fundamental topics in data science such as EDA automation, pipelines, ROC-AUC curve (how results will be evaluated), and Principal Component Analysis in a simple way. This contributes to its fast spread, difficult to treat, and tendency to re-occur. Figure 2: A quick look at the data.

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Machine Learning Data Analysis Data Science Automation 113

Flipboard

JUNE 8, 2023

In 2018, ISTE and General Motors launched a professional development course to train educators on how to use AI for teaching and learning. For his class on mathematical statistics, Ross asked his students to research theorems, their inventors and explain how the theorems were proved — without the help of AI.

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Robotics Auto-complete AI AI 176

Flipboard

MARCH 13, 2023

Yes, large language models (LLMs) hallucinate , a concept popularized by Google AI researchers in 2018. By looking at those strings of numbers, researchers can see how the model relates one concept to another, Sutskever explained. In short, you can’t trust what the machine is telling you.

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Mlearning.ai

MARCH 9, 2023

2018; Sitawarin et al., 2018; Papernot et al., 2018) investigated the vulnerability of deep learning models to adversarial attacks in medical image segmentation tasks, and proposed a method to improve their robustness. 2018; Pang et al., Explaining and harnessing adversarial examples. For instance, Xu et al.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

The following sections explain some of the primary steps with associated code. The financial analyst asks the following question: “ What are the closing prices of stocks AAAA, WWW, DDD in year 2018? Transcribe Audio Tool – To convert audio recordings to text files using Amazon Transcribe. WWW: $85.91 DDD: $9.82 WWW: $85.91 DDD: $9.82

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Flipboard

FEBRUARY 2, 2023

We then explain the details of the ML methodology and model training procedures. There are around 3,000 and 4,000 plays from four NFL seasons (2018–2021) for punt and kickoff plays, respectively. Models were trained and cross-validated on the 2018, 2019, and 2020 seasons and tested on the 2021 season.

Machine Learning 123

Machine Learning ML Big Data Data Scientist 123

DataRobot Blog

MAY 25, 2022

From 2018 to 2020, the U.S. Using either the code-centric DataRobot Core or no-code Graphical User Interface (GUI), both data scientists and non-data scientists such as risk analysts, government experts, or first responders can build, compare, explain, and deploy their own models. The scale and costs of weather disasters in the U.S.

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Marek Rei

NOVEMBER 12, 2019

ArXiv 2018. EMNLP 2018. NAACL 2018. NAACL 2018. At the end, I also include the summaries for my own published papers since the last iteration (papers 61-74). Here we go. Improving Language Understanding by Generative Pre-Training Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever. Microsoft, Edinburgh.

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Marek Rei

NOVEMBER 7, 2024

A recent survey paper by Calderon and Reichart [10] found that less than 10% of NLP interpretability papers consider inherently interpretable self-explaining models, with the authors advocating for more research on causal based interpretability methods. Weakly Supervised Explainable Phrasal Reasoning with Neural Fuzzy Logic.

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Explainability BERT NLP Large Language Models 90

AWS Machine Learning Blog

APRIL 3, 2023

Similarly, the nitrogen added as a fertilizer and the nitrogen leaching outcomes could be confounded as well, in the sense that a common cause can explain their association. In this crop yield study, the nitrogen added as fertilizer and the yield outcomes might be confounded. However, association is not causation.

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Inference Engine Machine Learning Algorithm Data Scientist 96

NYU Center for Data Science

OCTOBER 10, 2023

In a recent interview, Chen explained the importance of studying interpretability artifacts not just at the end of a model’s training but throughout its entire learning process. “A An MLM, BERT gained significant attention around 2018–2019 and is now often used as a base model fine-tuned for various tasks, such as classification.

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Mlearning.ai

MARCH 2, 2023

Moreover, the most important theoretical foundations for BERT are explained and additional graphics are provided for illustration purposes. In particular, the architecture of transformers and the attention mechanism, as well as the idea behind unsupervised transfer learning, especially with fine-tuning, are explained. 2] Vaswani, A.,

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Unite.AI

OCTOBER 1, 2024

What motivated you to launch SiLC, and what challenges did you set out to address when founding the company in 2018? Can you explain why Frequency Modulated Continuous Wave (FMCW) technology is critical for the next generation of AI-based machine vision? SiLC is your third Silicon Photonics startup.

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Robotics Automation Algorithm Explainability 130

Mlearning.ai

JANUARY 17, 2024

The foundations for today’s generative language applications were elaborated in the 1990s ( Hochreiter , Schmidhuber ), and the whole field took off around 2018 ( Radford , Devlin , et al.). The access to the GPT Store is for ChatGPT Plus users only (around $20 per month). You can create your own GPT and offer it to other users.

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Generative AI Prompt Engineering Prompt Engineer Large Language Models 98

IBM Journey to AI blog

OCTOBER 16, 2023

Before explaining data sovereignty, let us understand a broader concept—digital sovereignty—first. What do organizations need to do to in order to operate under these new sovereignty concepts? First, we must understand how data sovereignty came to be. What is data sovereignty? Data sovereignty in the EU is an evolving field.

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Categorization Explainability 232

Unite.AI

NOVEMBER 8, 2023

Interpretability and Explainability BERT : The bidirectional nature provides rich contextual embeddings but can be harder to interpret. GPT : Is generative in nature and can be prompted to perform tasks with minimal changes to its structure.

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NVIDIA

AUGUST 29, 2024

Soon after those papers were published in 2017 and 2018, Kiela and his team of AI researchers at Facebook, where he worked at that time, realized LLMs would face profound data freshness issues. This type of optimization opens up edge use cases with smaller computers that can perform at significantly higher-than-expected levels.

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Flipboard

JULY 10, 2023

By using our mathematical notation, the entire training process of the autoencoder can be written as follows: Figure 2 demonstrates the basic architecture of an autoencoder: Figure 2: Architecture of Autoencoder (inspired by Hubens, “Deep Inside: Autoencoders,” Towards Data Science , 2018 ). Or requires a degree in computer science?

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AWS Machine Learning Blog

OCTOBER 5, 2023

His research interests are in the area of natural language processing, explainable deep learning on tabular data, and robust analysis of non-parametric space-time clustering. From 2015–2018, he worked as a program director at the US NSF in charge of its big data program. He focuses on developing scalable machine learning algorithms.

Machine Learning 122

Machine Learning Big Data Deep Learning Natural Language Processing 122

AWS Machine Learning Blog

FEBRUARY 10, 2023

We describe how we designed an accurate, explainable ML model to make coverage classification from player tracking data, followed by our quantitative evaluation and model explanation results. Quantitative evaluation We utilize 2018–2020 season data for model training and validation, and 2021 season data for model evaluation.

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Mlearning.ai

FEBRUARY 19, 2023

GPT-3 is a successor to the earlier GPT-2 (released in Feb 2019) and GPT-1 (released in June 2018) models . As explained earlier, to get a better and robust model it has to be trained on large dataset. But it gained more prominence for being a model that generate human like text for a given set of words as input.

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