Flipboard

MAY 17, 2023

When are we going to have full (level-5) self-driving cars? And I think what they say, interestingly, is how much of our language is very much rote, R-O-T-E, rather than generated directly, because it can be collapsed down to this set of parameters. Or, how far can a person throw a Frisbee? I’ll give you that.

Large Language Models 182

Large Language Models Robotics Convolutional Neural Networks Neural Network 182

NVIDIA

OCTOBER 6, 2023

There’s a whole field of research that explores how to improve ETAS,” said Dacher-Cousineau, a postdoctoral researcher at UC Berkeley. It’s an immensely useful model that has been used a lot, but it’s been frustratingly hard to improve on it.” A research team is aiming to shake up the status quo for earthquake models.

Deep Learning 82

Deep Learning Natural Language Processing Neural Network Machine Learning 82

ODSC - Open Data Science

JULY 10, 2023

AI-enabled predictive analytics has transformed how teams function. Teams are leveraging the power of analytics to drive their revenue marketing goals through data-driven decisions. Think of how Amazon recommends products based on ‘customers also bought.’ Marketing tools like IBM Watson Studio, Adobe Analytics, etc.

AI 52

AI AI Data Science Artificial Intelligence 52

Viso.ai

FEBRUARY 13, 2024

Just like how we learn from our experiences, AI machines get better at their tasks as they gain more experience. According to the capabilities of AI, they are classified into three categories , which are Narrow AI, or Weak AI General AI, or Strong AI, and Artificial Superintelligence. To learn more, book a demo.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Computer Vision Natural Language Processing 52

Flipboard

MARCH 7, 2023

In an interview, Instagram co-founder Kevin Systrom explains what drew him to this space and how his new app’s underlying technology will serve to differentiate it from the competition. “I also witnessed the rise of TikTok and realized how important machine learning would be for the future of social.”

Machine Learning 122

Machine Learning Algorithm Explainability ChatGPT 122

Snorkel AI

MAY 3, 2023

This is a model trained on the Berkeley Deep Drive-100k dataset , performing bounding box tracking on the road. Whenever we see videos like this, we may get this overly positive impression of how remarkable deep learning models are, which is true in some cases. I would like to start the talk by showing you this video.

Machine Learning 52

Machine Learning Neural Network Explainability Data Scientist 52

Snorkel AI

MAY 3, 2023

This is a model trained on the Berkeley Deep Drive-100k dataset , performing bounding box tracking on the road. Whenever we see videos like this, we may get this overly positive impression of how remarkable deep learning models are, which is true in some cases. I would like to start the talk by showing you this video.

Machine Learning 52

Machine Learning Neural Network Explainability Data Scientist 52

Snorkel AI

JUNE 15, 2023

If you’re not familiar with how large consumer packaged goods companies work, a lot of times they’ll wait for certain trends to surface. All the techniques we use are common across these different categories. Someone’s talking about, for example, a turmeric latte. We do that on top of big sources of data.

Data Scientist 52

Data Scientist Machine Learning Data Science Large Language Models 52

Snorkel AI

JUNE 15, 2023

If you’re not familiar with how large consumer packaged goods companies work, a lot of times they’ll wait for certain trends to surface. All the techniques we use are common across these different categories. Someone’s talking about, for example, a turmeric latte. We do that on top of big sources of data.

Data Scientist 52

Data Scientist Machine Learning Data Science Large Language Models 52

AWS Machine Learning Blog

FEBRUARY 13, 2024

Also, when features used to train models offline in batch are made available for real-time inference, it’s hard to keep the two feature stores synchronized. In this post, we discuss the why and how of a centralized feature store with cross-account access. Features are inputs to ML models used during training and inference.

ML 105

ML ML Engineer Machine Learning Data Scientist 105

O'Reilly Media

APRIL 23, 2024

Why is it that Google, a company once known for its distinctive “Do no evil” guideline, is now facing the same charges of “surveillance capitalism” as Facebook, a company that never made such claims? Why is it now subject to the same kind of antitrust complaints faced by Microsoft, once the “evil empire” of the previous generation of computing?

BERT 108

BERT Algorithm AI AI 108

Ofemwire

NOVEMBER 21, 2023

With so many products competing for attention, it’s hard to make your product stand out. Additionally, how does this change impact fees, access to tools, and overall account management?” Can you provide a comprehensive guide on how to plan, produce, and optimize engaging storefront videos that resonate with customers?

ChatGPT 52

ChatGPT Algorithm AI AI 52

Mlearning.ai

FEBRUARY 15, 2024

How exactly can RPA in financial services aid companies address their challenges, and how can they implement those solutions for maximum prosperity? How exactly can RPA in financial services aid companies address their challenges, and how can they implement those solutions for maximum prosperity? billion by 2025.

Robotics 52

Robotics Automation Software Engineer Software Development 52

deepsense.ai

FEBRUARY 6, 2024

This task has applications in various fields such as medical analysis, autonomous driving, and augmented reality. Typically, we can classify segmentation tasks into four categories: Semantic Segmentation aims to associate a label with every pixel in an image.

Prompt Engineer 82

Prompt Engineer Prompt Engineering NLP Computer Vision 82

The MLOps Blog

DECEMBER 19, 2022

Traditional Machine Learning and Deep Learning methods are used to solve Multiclass Classification problems, but the model’s complexity increases as the number of classes increases. Particularly in Deep Learning, the network size increases as the number of classes increases. The product catalogue might have close to a million unique products.

ML 52

ML Deep Learning Algorithm Neural Network 52

AWS Machine Learning Blog

AUGUST 3, 2023

Use cases range from self-driving cars, content moderation on social media platforms, cancer detection, and automated defect detection. We demonstrate how you can combine well-known ML solutions with postprocessing to address this problem on the AWS Cloud. Both requirements are hard and costly to obtain.

Computer Vision 63

Computer Vision Data Scientist ML Deep Learning 63

Viso.ai

FEBRUARY 28, 2023

The OpenCV GPU module provides explicit control on how data is moved between CPU and GPU memory. Today, OpenCV is the de facto standard tool for image processing. Hence, the world’s leading companies across industries use OpenCV to develop their computer vision systems. What is Computer Vision? Get a demo here.

Computer Vision 52

Computer Vision Automation Algorithm Deep Learning 52

Explosion

AUGUST 3, 2017

It’s easy to reuse the code but hard to reuse the data, so building AI mostly means doing annotation. This is good, because the examples are how you program the behaviour – the learner itself is really just a compiler. Machine learning systems are built from both code and data. The net result is a lot of wasted effort.

Convolutional Neural Networks 52

Convolutional Neural Networks Python Machine Learning Algorithm 52

Unite.AI

NOVEMBER 7, 2023

One reason: slow, uninspiring innovation to 1950s-era industry standard components, lacking the kind of true disruptive technology breakthroughs that pushed so many other categories forward into the 21st century. Let’s dive into the specifics behind how this technology will truly harness the potential of innovation. The good news?

Automation 162

Automation AI AI 162

AI Impacts

NOVEMBER 23, 2022

If my guess is correct, then people first decide how doomy climate change is, and then they use this general factor of doom to answer the questions about severity, mitigation efforts, and geoengineering. Once they have a general factor of doom, it determines how they respond to specific questions they subsequently encounter.

Categorization 130

Categorization Explainability Machine Learning AI 130

ML Review

MARCH 31, 2019

Adversarial Patch”, a paper published at NIPS 2017 demonstrated how to generate a patch that can be placed anywhere within the field of view of the classifier and cause the classifier to output a targeted class. But by 2014, ConvNets had become powerful enough to start surpassing human accuracy on a number of visual recognition tasks.

Neural Network 52

Neural Network Machine Learning Deep Learning Explainability 52

Cold Takes

JUNE 23, 2022

Writing about ideal governance reminded me of how weird my experiences with nonprofit boards (as in "board of directors" - the set of people who formally control a nonprofit) have been. Why nonprofit boards are weird Here's how a nonprofit board works: There are usually 3-10 people on the board (though sometimes much more).

Explainability 59

Explainability 59

Mlearning.ai

FEBRUARY 24, 2024

Which AI technologies will be regulated and how? How will generative AI be dealt with? How bad is it? The final revisions are underway and the EU Parliament is expected to adopt the new EU AI Act in the coming weeks. What does this mean for the European AI scene? My article is about the following: What does the Act regulate?

AI 98

AI AI Generative AI ChatGPT 98

AWS Machine Learning Blog

SEPTEMBER 5, 2023

We use the powerful generating capability of LLMs to generate the final decision including safe/unsafe labels and category type. The designed prompt template allows the LLM to determine if the image violates the moderation policy, identify the category of violation, explain why, and provide the output in a structured JSON format.

Generative AI 95

Generative AI LLM ML Computer Vision 95

AI Impacts

DECEMBER 22, 2022

Others: wow that sounds extremely ambitious Some people: yeah but it's very important and also we are extremely smart so idk it could work [Work on it for a decade and a half] Some people: ok that's pretty hard, we give up Others: oh huh shouldn't we maybe try to stop the building of this dangerous AI?

AI 130

AI AI AI Researcher AI Research 130

ODSC - Open Data Science

FEBRUARY 8, 2024

An AI strategy is a framework that will help the organization understand what data-driven projects and data sources are the most valuable to the organization, and how to prioritize them to build toward their product vision over time. How can we build up toward our vision in terms of solvable data problems and specific data products?

AI Strategy 52

AI Strategy Data Scientist Data Science AI 52

Cold Takes

DECEMBER 8, 2022

Unfortunately, I think it could be hard to know either way. and to potentially appear safer than they are - so I think it will be hard to be as cautious about AI as we should be. When dealing with an intelligent agent, it’s hard to tell the difference between “behaving well” and “ appearing to behave well.”

AI 59

AI AI AI Developer AI Development 59

The MLOps Blog

OCTOBER 3, 2023

How to transition from data analytics to MLOps engineering Piotr: Miki, you’ve been a data scientist, right? How did you manage to jump from a more analytical, scientific type of role to a more engineering one? How did you manage to jump from a more analytical, scientific type of role to a more engineering one?

ML 52

ML Data Scientist Machine Learning Data Science 52

O'Reilly Media

NOVEMBER 28, 2023

And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. Our survey focused on how companies use generative AI, what bottlenecks they see in adoption, and what skills gaps need to be addressed.

Generative AI 108

Generative AI AI AI Data Analysis 108

Unite.AI

FEBRUARY 7, 2024

If you're a photographer or graphic designer, you probably know all too well how complicated, expensive, and frustrating editing photos can be. In this Skylum Luminar Neo Review, I'll discuss what it is, who it's best for, and how to create an account to download Luminar Neo. Shouldn't editing photos be fun and effortless?

AI Tools 130

AI Tools AI AI Artificial Intelligence 130

BAIR

MAY 3, 2022

How do we build and evaluate an AI system for real-world applications? In other words, we need to incorporate human effort/annotations regardless of how the models perform on previous testing sets. reliability); and 3) the percentage of novel categories that are detected as low-confidence predictions (i.e.,

AI Modeling 147

AI Modeling Automation AI Developer AI Development 147

DataRobot Blog

NOVEMBER 3, 2022

Workers estimate how long it will take to get to and from work, then arrange their day around that forecast. It takes something that’s hard to do but important to get right — forecasting — and supercharges data scientists. Data scientists have used the DataRobot AI Cloud platform to build time series models for several years.

Data Scientist 52

Data Scientist Black Box AI Explainability Automation 52

AWS Machine Learning Blog

JUNE 27, 2023

When machine learning (ML) models are deployed into production and employed to drive business decisions, the challenge often lies in the operation and management of multiple models. This blog post is co-written with Marat Adayev and Dmitrii Evstiukhin from Provectus. The models developed by Earth.com lived across various notebooks.

DevOps 94

DevOps ML Machine Learning Automation 94

Cold Takes

JANUARY 13, 2023

This post will lay out a couple of stylized stories about how, if transformative AI is developed relatively soon, this could result in global catastrophe. (By Click lower right to download or find on Apple Podcasts, Spotify, Stitcher, etc. When early problems arise, they react to these problems.

AI 59

AI AI Robotics AI Developer 59

Snorkel AI

JUNE 22, 2023

In the last 12 years, how we build and how we do the work that we do has changed quite a few times. I’m joined by Brian Richardson, who’s an Associate Partner, and Senior Data Scientist at Quantum Black, and also leads our data-centric AI efforts across Quantum Black and McKinsey globally. The macro view will not be surprising.

Data Quality 52

Data Quality Automation Data Scientist ML 52

Snorkel AI

JUNE 22, 2023

In the last 12 years, how we build and how we do the work that we do has changed quite a few times. I’m joined by Brian Richardson, who’s an Associate Partner, and Senior Data Scientist at Quantum Black, and also leads our data-centric AI efforts across Quantum Black and McKinsey globally. The macro view will not be surprising.

Data Quality 52

Data Quality Automation Data Scientist ML 52

Snorkel AI

DECEMBER 14, 2023

Even after training an initial model, teams struggle with model-centric iteration, an inefficient “whack-a-mole” process to drive down errors on rare but critical data slices. Building enterprise-grade AI: use a data-centric approach AI rarely works out of the box for enterprise applications. We call this “data-centric” AI.

Categorization 64

Categorization Prompt Engineer Prompt Engineering Data Science 64