AI Weekly

SEPTEMBER 14, 2023

technologyreview.com AI technology behind ChatGPT was built in Iowa — with a lot of water The cost of building an artificial intelligence product like ChatGPT can be hard to measure. Plus, they feed insights that have pulled in an extra $250k in ARR per rep. Start automating your sales today!]

Robotics 218

Robotics Artificial Intelligence Artificial Intelligence Machine Learning 218

Towards AI

NOVEMBER 7, 2023

Among big tech, Google, Microsoft (Open AI), and Amazon have proprietary products, while Meta (Facebook) and NVIDIA offer open-source models. Differences to take into account would not be only between open-source and closed-source but also within the two categories. proprietary) offerings.

Generative AI 112

Generative AI AI AI AI Modeling 112

AWS Machine Learning Blog

SEPTEMBER 7, 2023

Efficient control policies enable industrial companies to increase their profitability by maximizing productivity while reducing unscheduled downtime and energy consumption. In offline reinforcement learning, one can train a policy on historical data before deploying it into production. Train the algorithm on that data.

Natural Language Processing 94

Natural Language Processing Machine Learning Algorithm Automation 94

PyImageSearch

DECEMBER 29, 2022

Grooming is taking your product’s to-do list of work and transforming it into a product backlog. Example of well groomed backlog Here’s a quick example of a few product backlog items (PBIs) that have not groomed and a few that have. Grooming your backlog Let’s start with a quick working definition.

Explainability 52

Explainability Categorization Automation 52

AWS Machine Learning Blog

MAY 5, 2023

To create this app, they need a high-quality dataset containing clothing images, labeled with different categories. To generate the official Fashion200K dataset, the dataset’s authors crawled more than 300,000 products online, and only products with descriptions containing more than four words made the cut.

Metadata 75

Metadata Computer Vision Machine Learning Data Scientist 75

Snorkel AI

JUNE 30, 2023

Jack Zhou, product manager at Arize , gave a lightning talk presentation entitled “How to Apply Machine Learning Observability to Your ML System” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. I’m a product manager at Arize. As you’re probably aware, the road to production is pretty challenging.

Machine Learning 52

Machine Learning ML Data Quality Data Drift 52

Snorkel AI

JUNE 30, 2023

Jack Zhou, product manager at Arize , gave a lightning talk presentation entitled “How to Apply Machine Learning Observability to Your ML System” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. I’m a product manager at Arize. As you’re probably aware, the road to production is pretty challenging.

Machine Learning 52

Machine Learning ML Data Quality Data Drift 52

Towards AI

MAY 12, 2023

Datasets Usually, text classification tasks solved in production have two characteristics: they are unique (have never been “seen” before) and hard to describe using a strict set of rules. We picked PromptSource — one of the biggest open prompt bases, containing 170+ English datasets.

Prompt Engineer 81

Prompt Engineer Prompt Engineering Large Language Models LLM 81

TheSequence

MAY 29, 2023

If you use scraped data, the model might pick up some private information, amplify existing biases, and, consequently, create more harm than good. The final product, StarCoder, is the StarCoderBase model fine-tuned on the data sourced from the same dataset. We used a similar system for tasks in production.

LLM 52

LLM Responsible AI Natural Language Processing Software Engineer 52

Artificial Corner

JANUARY 11, 2024

In case you don’t have a specific GPT in mind, you can explore the top pick for categories such as writing, productivity, programming, education, and more. Trying any of them is as simple as clicking on the GPT and then following the instructions written by the builder.

OpenAI 52

OpenAI ChatGPT AI AI 52

Mlearning.ai

SEPTEMBER 4, 2023

import pandas as pd # Creating a sample DataFrame data = {'Product': ['A', 'B', 'C', 'D'], 'SalesAmount': [1200, 800, 1500, 600]} df = pd.DataFrame(data) # Filtering data where SalesAmount is greater than 1000 filtered_data = df[df['SalesAmount'] > 1000] print(filtered_data) 2.

Python 52

Python Categorization Machine Learning Data Analysis 52

Flipboard

NOVEMBER 28, 2023

A helpful starting point when developing these scales might be the NIST RMF, which suggests using qualitative nonnumerical categories ranging from very low to very high risk or semi-quantitative assessments principles, such as scales (such as 1–10), bins, or otherwise representative numbers.

Responsible AI 144

Responsible AI Artificial Intelligence Artificial Intelligence AI 144

Heartbeat

FEBRUARY 7, 2023

Language models can be divided into two categories: Statistical language models Neural language models Statistical Language Models Based on probability theory, statistical language models calculate the likelihood of a word sequence using statistical methods. How does the team at Uber manage to keep their data organized and their team united?

NLP 52

NLP Neural Network Deep Learning BERT 52

Viso.ai

DECEMBER 20, 2023

In image recognition , supervised learning algorithms are used to learn how to identify a particular object category (e.g., “person”, “car”, etc.) For example, you can use supervised learning for image classification , where algorithms learn to classify data into different categories (e.g., from a set of images.

Computer Vision 98

Computer Vision Neural Network Machine Learning Algorithm 98

Snorkel AI

JUNE 15, 2023

At Black Swan Data, we’re a company that helps predict what products haven’t been made yet but should be made. Eventually, they’ll do a classic survey, so they’ll ask a small set of people, 100-500, some different questions about products they might be interested in. A transcript of the talk follows.

Data Scientist 52

Data Scientist Machine Learning Data Science Large Language Models 52

Snorkel AI

JUNE 15, 2023

At Black Swan Data, we’re a company that helps predict what products haven’t been made yet but should be made. Eventually, they’ll do a classic survey, so they’ll ask a small set of people, 100-500, some different questions about products they might be interested in. A transcript of the talk follows.

Data Scientist 52

Data Scientist Machine Learning Data Science Large Language Models 52

Heartbeat

FEBRUARY 21, 2023

Among other things, companies use it to get insight from their customers on social media and know what is being said about their products. Sentiment Analysis One common approach to sentiment analysis is using supervised machine learning techniques to classify text into various sentiment categories, such as positive, negative, or neutral.

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics Machine Learning 52

Unite.AI

NOVEMBER 17, 2023

These features can be divided into three categories: Editor Text & Speech AI Avatars Let's take a closer look at these features. AI Script Assistant Use the AI Script assistant ( GPT-3 ) to generate ideas, enhance messaging, fix grammar, and boost video production in any major language. Here's how it turned out! 70+ languages.

AI 274

AI AI Natural Language Processing Auto-complete 274

Mlearning.ai

APRIL 17, 2023

In this paper, the dataset is described as containing 590,540 labeled credit card transactions and was extracted from a production fraud detection system. astype('category').cat.as_ordered() astype('category').cat.as_ordered() astype(int) + data['card2'].astype(int) astype(int) + data['addr1'].astype(int)

Neural Network 52

Neural Network Categorization Algorithm Python 52

AWS Machine Learning Blog

AUGUST 3, 2023

For example, on online shopping platforms, the angle at which products are shown in images has an effect on the rate of buying this product. If you have a team of data scientists, they might also want to enhance the models further and pick a more custom and flexible option. One such case is to detect the position of a car.

Computer Vision 63

Computer Vision Data Scientist ML Deep Learning 63

Mlearning.ai

FEBRUARY 9, 2023

What model would you pick? Now let’s say the business has the most users consuming news and sports content, and it is more important for your company to do better in those categories. Often, the business and product managers are looking for guidance from you, as they don’t understand the data and data science as well as you do.

Data Scientist 52

Data Scientist Data Science ML Machine Learning 52

Unite.AI

JUNE 30, 2023

This tailored feedback in the moment allows agents to build a relationship with the customer based on that particular customer’s experience and their voice signals picked up by the AI model. Cogito uses a ‘fairness’ dataset comprised of a large body of audio data where the speakers self-report different demographic categories.

Emotion AI 296

Emotion AI Machine Learning Conversational AI Natural Language Processing 296

Cold Takes

JUNE 30, 2022

I selected them by vaguely remembering that "the Big Three of science fiction" is a thing people say sometimes, googling it, and going with who came up - no hunting around for lots of sci-fi authors and picking the best or worst. 6 All of these are predictions Asimov made in 1964, about the year 2014 (unless otherwise indicated).

AI 52

AI AI Robotics AI Researcher 52

The MLOps Blog

FEBRUARY 22, 2024

Check out my example project or visit the product website to learn more. Adopting CL in production environments is beneficial but challenging. Most ML systems in production today do not fully use continual learning but remain in lower stages. See in the app Full screen preview Neptune.ai Experiment as much as you can.

Continuous Learning 59

Continuous Learning Machine Learning ML Neural Network 59

Explosion

AUGUST 3, 2017

prodigy dataset gh_issues "Classify issues on GitHub" prodigy textcat.teach gh_issues en_core_web_sm "docs" --api github --label DOCS Opening localhost:8080 , we get a sequence of recent GitHub issue titles, displayed with our category as the title. If the category is correct, click accept , press a , or swipe left on a touch interface.

Convolutional Neural Networks 52

Convolutional Neural Networks Python Machine Learning Algorithm 52

The MLOps Blog

JANUARY 5, 2023

3 Things to keep in mind while designing visual search engines 4 Importance of embeddings in visual search 5 Evaluation of visual search engines 6 Integrating visual search engines with other products 7 Basic tool stack for building visual search engines 8 Scaling visual search systems 9 … and more! All right, let’s get to it.

Computer Vision 52

Computer Vision Machine Learning ML Explainability 52

ODSC - Open Data Science

JUNE 21, 2023

Simplifying Time Series Forecasting: Replicating Monsaraida’s Solution on Kaggle for Retail Volume Predictions The M5 Competition, hosted on Kaggle, has recently drawn attention to the effectiveness of gradient-boosting methods for volume forecasts of retail products. sum() / 1024**2 for col in df.columns: col_type = df[col].dtypes

Data Science 96

Data Science Data Scientist Computer Scientist AI 96

AWS Machine Learning Blog

JUNE 7, 2023

Our product team wants us to determine the most critical metrics that influence a shopper’s purchase decision. Administrative_Duration Numeric Amount of time spent in this category of pages. Informational_Duration Numeric Amount of time spent in this category of pages. Revenue Binary If a purchase was made. Select the dataset.

ML 67

ML Automation Auto-complete Categorization 67

Topbots

SEPTEMBER 11, 2023

The model serves as a tool for the discussion, planning, and definition of AI products by cross-disciplinary AI and product teams, as well as for alignment with the business department. It aims to bring together the perspectives of product managers, UX designers, data scientists, engineers, and other team members.

AI 59

AI AI UX Design Automation 59

Marktechpost

JULY 17, 2023

For instance, forecasting the sales of a product (let’s say flowers) on a specific day in a market, There would be a lot more rose sales if it were Valentine’s Day! AI picks up knowledge by acquiring it, then applies it to new judgments. Through practice, machines pick up information or skills (or data).

Machine Learning 98

Machine Learning Data Mining Data Scientist Artificial Intelligence 98

The MLOps Blog

OCTOBER 3, 2023

I actually did not pick up Python until about a year before I made the transition to a data scientist role. Can I go back and pick up the other option?” How do I get this model in production? Mikiko Bazeley: With most boot camps, it comes down to picking the right one, honestly. And usually, the answer is “yes, you can.”

ML 52

ML Data Scientist Machine Learning Data Science 52

Marktechpost

MAY 10, 2024

The skilled professionals at MakeML will assist you in developing a Computer Vision solution and incorporating it into your product. SageMaker Canvas may then make predictions and put the trained model into production. Data Robot’s flexible features make it a solid pick for those with little programming experience.

AI Tools 116

AI Tools Machine Learning Artificial Intelligence Artificial Intelligence 116

Robot Writers AI

MARCH 31, 2024

That remarkable candor pretty much set the tone for Q1 2024, during which writers saw automation picking-off good paying writing jobs faster than they could say ‘Take me to your AI overlord.’ The Pulitzer Board only added this requirement to the journalism category.” *AI

Auto-complete 52

Auto-complete Robotics ChatGPT AI 52

AWS Machine Learning Blog

MAY 7, 2024

Sub-intents and intent trees If you make the preceding scenario more complex, as in many real-life use cases, intents can be designed in a large number of categories and also in a hierarchical fashion, which will make the classification tasks more challenging for the model. customer_interactions = [ "I want to change my coverage plan.

Prompt Engineer 95

Prompt Engineer Prompt Engineering Large Language Models LLM 95

DataRobot Blog

NOVEMBER 3, 2022

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. This helps to scale the impact of each data scientist’s time and shortens the time to get models into production. . Enable Granular Forecasts with Clustering. Maybe it’s time-consuming.

Data Scientist 52

Data Scientist Black Box AI Explainability Automation 52

DataRobot Blog

MARCH 9, 2022

This article may not be entirely up-to-date or refer to products and offerings no longer in existence. The Amazon Product Reviews Dataset provides over 142 million Amazon product reviews with their associated metadata, allowing machine learning practitioners to train sentiment models using product ratings as a proxy for the sentiment label.

Machine Learning 52

Machine Learning Neural Network Convolutional Neural Networks Deep Learning 52

Mlearning.ai

AUGUST 11, 2023

You don’t need to use everything, just pick and choose what you need. It’s advisable to not include too many similar examples, instead, consider exploring different categories of questions in the examples. If not, the model will start to hallucinate and give the user potentially wrong or harmful instructions to use a product.

Prompt Engineer 98

Prompt Engineer Prompt Engineering Robotics ChatGPT 98