Unite.AI

OCTOBER 17, 2023

Without this purpose, it is hard for an AI-run process to be effective. For the segmentation process to work, after validating the model’s accuracy, you need to review the different segments and determine whether the variables driving those segments adequately apply to your business model.

AI 277

AI AI Machine Learning Algorithm 277

ODSC - Open Data Science

JULY 10, 2023

Teams are leveraging the power of analytics to drive their revenue marketing goals through data-driven decisions. For instance, analyzing previous purchases and browsing history can let the AI predict what product category can interest a particular set of customers and thereby suggest relevant items.

AI 52

AI AI Data Science Artificial Intelligence 52

O'Reilly Media

APRIL 4, 2024

To the extent that entrepreneurial funding is more concentrated in the hands of a few, private finance can drive markets independent of consumer preferences and supply dynamics. This is using capital properly: to fund the hard costs associated with creating something new until the projected unit economics lead to a self-sustaining business.

OpenAI 61

OpenAI AI AI Artificial Intelligence 61

Flipboard

MAY 17, 2023

When are we going to have full (level-5) self-driving cars? My understanding is that Microsoft’s initial investment was in time on the cloud computing rather than hard, cold cash. Same with truck driving…. In fact, six or seven years ago, there were predictions that we would have fully self-driving cars by now.

Large Language Models 182

Large Language Models Robotics Convolutional Neural Networks Neural Network 182

Viso.ai

FEBRUARY 13, 2024

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. Despite commonalities, significant distinctions exist among these three categories. What are the 3 Types of Artificial Intelligence?

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Computer Vision Natural Language Processing 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. To see what I mean, let’s think about how you would build and deploy a self-driving car model. Here, the output typically contains some predefined categories such as pedestrians and cars and trucks, and so on.

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. To see what I mean, let’s think about how you would build and deploy a self-driving car model. Here, the output typically contains some predefined categories such as pedestrians and cars and trucks, and so on.

Machine Learning 52

Machine Learning Neural Network Explainability Data Scientist 52

Snorkel AI

JUNE 15, 2023

All the techniques we use are common across these different categories. I want to talk about this hard area in the middle (Filter). I have a brief analogy that I shared with my team to drive this home. Then we could compose that with other category distinctions that we’re making.

Data Scientist 52

Data Scientist Machine Learning Data Science Large Language Models 52

Snorkel AI

JUNE 15, 2023

All the techniques we use are common across these different categories. I want to talk about this hard area in the middle (Filter). I have a brief analogy that I shared with my team to drive this home. Then we could compose that with other category distinctions that we’re making.

Data Scientist 52

Data Scientist Machine Learning Data Science Large Language Models 52

Flipboard

MARCH 7, 2023

” Instead, Artifact has selected the top publishers across different categories to fuel the content in the app. Artifact’s recommendation system Image Credits: Artifact Systrom credits Toutiao for driving innovation in recommendation systems, noting that Toutiao essentially helped ByteDance give birth to TikTok.

Machine Learning 122

Machine Learning Algorithm Explainability ChatGPT 122

The MLOps Blog

DECEMBER 19, 2022

Metric Learning problems principally fall into two categories one is Supervised where data points have a class label as target (same as in standard classification problem), and another one is Weakly Supervised where data points are at tuple level (pairs, triplets or quadruplets). Hence, this leads to an increase in inference time as well.

ML 52

ML Deep Learning Algorithm Neural Network 52

Mlearning.ai

FEBRUARY 15, 2024

Financial robots keep evolving from specific task automation to entire process automation that drives financial analysis and prognosis accuracy. Even such strategic functions as business development and external relations can partly be performed by technology, though, to a substantially lesser percentage than the previous categories.

Robotics 52

Robotics Automation Software Engineer Software Development 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. There are two distinct categories of permissions associated with sharing resources: Discoverability permissions – Discoverability means being able to see feature group names and metadata.

ML 104

ML ML Engineer Machine Learning Data Scientist 104

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. Both requirements are hard and costly to obtain. Computer vision (CV) is one of the most common applications of machine learning (ML) and deep learning.

Computer Vision 63

Computer Vision Data Scientist ML Deep Learning 63

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

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. The good news? At its core, this generational architecture upgrade is a classic Silicon Valley semiconductor story.

Automation 162

Automation AI AI 162

O'Reilly Media

APRIL 23, 2024

Google and Amazon were still atop their respective hills of web search and ecommerce in 2010, and Meta’s growth was still accelerating, but it was hard to miss that internet growth had begun to slow. There is little space left for organic results at the top of the page, the real estate that drives most sales. The market was maturing.

BERT 108

BERT Algorithm AI AI 108

Viso.ai

FEBRUARY 28, 2023

While most are aware of rather popular use cases in security and video surveillance or self-driving cars, fewer people get to see the use cases in specific industries such as industrial manufacturing or retail analytics. Driving upgrades to faster processors would generate more income for Intel than selling some extra software.

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. During that time, spaCy has grown into the most popular library of its type, giving us a lot of insight into what’s driving success and failure for language understanding technologies.

Convolutional Neural Networks 52

Convolutional Neural Networks Python Machine Learning Algorithm 52

ML Review

MARCH 31, 2019

Let’s quickly look at two categories of defenses that have been proposed so far: Adversarial training One of the easiest and most brute-force way to defend against these attacks is to pretend to be the attacker, generate a number of adversarial examples against your own network, and then explicitly train the model to not be fooled by them.

Neural Network 52

Neural Network Machine Learning Deep Learning Explainability 52

Ofemwire

NOVEMBER 21, 2023

With so many products competing for attention, it’s hard to make your product stand out. Can you provide insights into the unique challenges and opportunities associated with different product categories on Amazon, and guide me on tailoring my selling strategies to align with the expectations of customers in specific niches?

ChatGPT 52

ChatGPT Algorithm AI AI 52

AI Impacts

NOVEMBER 23, 2022

How hard of a takeoff will we see after AGI is developed? How hard is it for people to teach a value system to an AI? How hard is it to make an AGI corrigible? How hard is it to design a good governance mechanism for AI capabilities research? How fragile are good values? Are two similar ethical systems similarly good?

Categorization 130

Categorization Explainability Machine Learning AI 130

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 94

Generative AI LLM ML Computer Vision 94

Mlearning.ai

FEBRUARY 24, 2024

Risk categories in the EU AI Act: Prohibited, high risk, systemic risk, limited risk, minimal risk Based on the risk assessment, what does a company need to do when developing AI solutions? There are many regulations here, most of which are listed under high-risk applications: EU AI Act: What regulations exist for which risk categories?

AI 98

AI AI Generative AI ChatGPT 98

ODSC - Open Data Science

FEBRUARY 8, 2024

Example AcmeMealCo identifies several categories where data products could support a customer with their meal preparation. The data scientists repeat this process for all of the categories they identified in Step 3. It might be helpful to use different types of edges to capture ‘hard’ dependencies (i.e.

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

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

Cold Takes

JUNE 23, 2022

OK, so what's driving the weirdness? If a nonprofit is a year old and has 3 employees, it probably shouldn't be investing a ton of its energy in having a great board (especially since this is hard). Not a big enough deal: most other stuff in this category. Keeping it simple for low-stakes organizations.

Explainability 59

Explainability 59

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. The plant category was selected first for implementation. This blog post is co-written with Marat Adayev and Dmitrii Evstiukhin from Provectus.

DevOps 94

DevOps ML Machine Learning Automation 94

BAIR

MAY 3, 2022

reliability); and 3) the percentage of novel categories that are detected as low-confidence predictions (i.e., At first, we believed that, ideally, AI should fully replace human effort in simple and tedious tasks such as large-scale image recognition and car driving. We think it is not cheating or surrendering to hard problems.

AI Modeling 147

AI Modeling Automation AI Developer AI Development 147

O'Reilly Media

NOVEMBER 28, 2023

Executive Summary We’ve never seen a technology adopted as fast as generative AI—it’s hard to believe that ChatGPT is barely a year old. It’s hard to imagine a business where AI couldn’t be put to use, and it can’t be healthy to a company’s long-term success to ignore that promise. Is that the issue? of nonusers and 13% of users.

Generative AI 108

Generative AI AI AI Data Analysis 108

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. It’s often hard to define the final schema until you explore the data and adjust accordingly. Snorkel Flow offers several tools for this.

Categorization 64

Categorization Prompt Engineer Prompt Engineering Data Science 64

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. It’s often hard to define the final schema until you explore the data and adjust accordingly. Snorkel Flow offers several tools for this.

Categorization 59

Categorization Prompt Engineer Prompt Engineering Data Science 59

DataRobot Blog

NOVEMBER 3, 2022

It takes something that’s hard to do but important to get right — forecasting — and supercharges data scientists. This takes the redundant, time-consuming work of creating a model for each store, SKU, or category, and reduces that work to a handful of clicks. But sometimes you don’t want to rely on human intuition to define segments.

Data Scientist 52

Data Scientist Black Box AI Explainability Automation 52

The MLOps Blog

OCTOBER 3, 2023

Mikiko Bazeley: I think it comes down to understanding the different types of feature stores that are out there, and even understanding why a virtual feature store is maybe just a terrible name for what FeatureForm is category-wise; it’s not very descriptive. At that point, it was very hard to do things.

ML 52

ML Data Scientist Machine Learning Data Science 52

Cold Takes

JANUARY 13, 2023

It’s hard to talk about risks from transformative AI because of the many uncertainties about when and how such AI will be developed - and how much the (now-nascent) field of “AI safety research” will have grown by then, and how seriously people will take the risk, etc. Will this transfer to when AIs are in control ?

AI 59

AI AI Robotics AI Developer 59

Unite.AI

FEBRUARY 7, 2024

From there, I will discuss all its features with examples from each category so you know everything it can do. Before downloading, ensure you have enough space on your computer (you'll need roughly 10 GB on your hard drive). I went to “My software” in my Skylum account and selected “Download.”

AI Tools 130

AI Tools AI AI Artificial Intelligence 130