NYU Center for Data Science

JUNE 16, 2023

Home to both a thriving tech ecosystem and pioneering efforts on regulating algorithm decision-making systems, New York City provides a vibrant research environment and a plethora of interdisciplinary collaborators,” said Umang. For these reasons, I am excited to start my academic journey at NYU. By Meryl Phair

Machine Learning 106

Machine Learning Artificial Intelligence Artificial Intelligence Explainability 106

Unite.AI

SEPTEMBER 29, 2023

Lucky for you, this comprehensive Murf AI review will explain how you can use AI voice generation to elevate your content creation to a whole new level! I'll explain Murf AI's key features and show you how easy they are to use. You can also adjust the pitch, speed, and more exactly how you'd like to get the most human-like result.

AI 247

AI AI Explainability Automation 247

DataRobot Blog

DECEMBER 7, 2019

which indicates very strong predictive power for the 2020 offseason, assuming no major shifts in the negotiating positions of players and teams from the last decade. We believe AI is only as good as it is explainable, so the charts below show which variables our AI relied on the most to predict AAV for both pitchers and position players.

Machine Learning 52

Machine Learning Explainability AI Modeling Artificial Intelligence 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. ” This, he explains, was basically a “follow graph” powered by machine learning, instead of by users clicking a button.

Machine Learning 145

Machine Learning Algorithm Explainability ChatGPT 145

NVIDIA

AUGUST 29, 2024

So, in the spring of 2020, Kiela and his team published a seminal paper of their own, which introduced the world to retrieval-augmented generation. In many ways, it’s an advanced, productized version of the RAG architecture Kiela and Singh first described in their 2020 paper. The platform Contextual AI offers is called RAG 2.0.

Neural Network 93

Neural Network LLM Large Language Models OpenAI 93

Heartbeat

SEPTEMBER 13, 2023

Source: ResearchGate Explainability refers to the ability to understand and evaluate the decisions and reasoning underlying the predictions from AI models (Castillo, 2021). Explainability techniques aim to reveal the inner workings of AI systems by offering insights into their predictions. What is Explainability?

Explainability 52

Explainability Machine Learning Deep Learning Explainable AI 52

IBM Journey to AI blog

JULY 19, 2023

IBM Consulting has been driving a responsible and ethical approach to AI for more than five years now, mainly focused on these five basic principles: Explainability : How an AI model arrives at a decision should be able to be understood, with human-in-the-loop systems adding more credibility and help mitigating compliance risks.

Generative AI 183

Generative AI Large Language Models AI AI 183

IBM Journey to AI blog

OCTOBER 9, 2023

IBM has long argued that AI systems need to be transparent and explainable. Such features will help address many of the same concerns as proposed legislation under consideration to address copyright protection, privacy and algorithmic bias.

Automation 138

Automation AI AI Natural Language Processing 138

PyImageSearch

DECEMBER 9, 2024

This lesson is the last of a 3-part series on 3D Reconstruction: Photogrammetry Explained: From Multi-View Stereo to Structure from Motion NeRFs Explained: Goodbye Photogrammetry? Essentially, you send 30+ input images to an SfM algorithm, and it returns a point cloud. 2023 ) See how we added 3 blocks? Thats A, B, and C.

Computer Vision 95

Computer Vision Deep Learning Explainability Algorithm 95

Flipboard

FEBRUARY 16, 2023

To create NLP models, developers need not only algorithms, but bucketloads of quality training data that is accurately “labelled,” a technique that categorizes raw data to enable machines to understand and learn from it. . million ($2.9

NLP 123

NLP Data Scientist Natural Language Processing AI 123

PyImageSearch

JUNE 12, 2023

Home Table of Contents DETR Breakdown Part 2: Methodologies and Algorithms The DETR Model ?️ Summary Citation Information DETR Breakdown Part 2: Methodologies and Algorithms In this tutorial, we’ll learn about the methodologies applied in DETR. 2020) propose the following algorithm. Optimal Bipartite Matching ?

Algorithm 60

Algorithm Computer Vision Deep Learning Artificial Intelligence 60

Unite.AI

JULY 26, 2023

Given that persona, explain the key events and reasons leading to the downfall of the French monarchy.” For instance, a user might be interested in the potential impact of artificial intelligence on job markets: User : “Could you briefly explain the concept of artificial intelligence?”

Prompt Engineer 246

Prompt Engineer Prompt Engineering ChatGPT Large Language Models 246

AWS Machine Learning Blog

NOVEMBER 26, 2024

We use the following prompt to read this diagram: The steps in this diagram are explained using numbers 1 to 11. Can you explain the diagram using the numbers 1 to 11 and an explanation of what happens at each of those steps? Architects could also use this mechanism to explain the floor plan to customers.

Convolutional Neural Networks 113

Convolutional Neural Networks LLM Metadata Explainability 113

ODSC - Open Data Science

OCTOBER 24, 2023

Then, how to essentially eliminate training, thus speeding up algorithms by several orders of magnitude? My NoGAN algorithm, probably for the first time, comes with the full multivariate KS distance to evaluate results. Indeed, the whole technique epitomizes explainable AI. It is adjusted for dimension.

Categorization 98

Categorization Data Science Neural Network Algorithm 98

Unite.AI

JUNE 17, 2024

Machine learning algorithms can analyze vast amounts of transaction data in real-time, identifying patterns and anomalies that might indicate fraudulent activity. Algorithms can analyze market data, news sentiment, and social media trends to predict stock prices and optimize portfolio allocation.

Automation 148

Automation Artificial Intelligence Artificial Intelligence Explainability 148

NVIDIA

NOVEMBER 20, 2023

Advanced congestion control using real-time telemetry data and network-aware algorithms to manage and prevent congestion in AI networks. Since their introduction in 2020, DPUs have gained popularity in the realm of cloud computing, primarily due to their capacity to offload, accelerate and isolate data center infrastructure processing.

Large Language Models 134

Large Language Models Generative AI Algorithm AI 134

AI Impacts

FEBRUARY 1, 2023

A faulty brake line on a car is not much of a concern to the public until the car is on public roads, and the facebook feed algorithm cannot be a threat to society until it is used to control what large numbers of people see on their screens. But this model, on its own, is inadequate for AI, for reasons I will explain in the next section.

AI 130

AI AI OpenAI Large Language Models 130

Unite.AI

FEBRUARY 16, 2024

Since its launch in 2020, the Buddy app has won several awards and topped the charts in the App Store's Kids and Education category with over 36M downloads worldwide. Children download the App and convince parents to pay for a subscription, explaining that Buddy is a teacher.

Natural Language Processing 174

Natural Language Processing UX Design AI AI 174

ODSC - Open Data Science

APRIL 4, 2023

Amazon’s scrapped hiring AI model infamously penalized women’s resumes as the machine learning algorithm expanded on implicit biases within the training data. More than half of organizations in 2020 took steps to mitigate AI concerns, a three-point increase over 2019. Thankfully, the world is moving in this direction.

Black Box AI 98

Black Box AI Data Science AI AI 98

AWS Machine Learning Blog

MARCH 23, 2023

For more information, check out the video How would you explain homomorphic encryption? To learn more about the FHE public key encryption process we chose, refer to CKKS explained. The AWS re:Invent 2020 breakout session Privacy-preserving maching learning , by Joan Feidenbaim, Amazon Scholar with the AWS Crytographic Algorithms Group.

ML 127

ML Machine Learning Deep Learning Explainability 127

The Stanford AI Lab Blog

FEBRUARY 24, 2022

2020 , Sohn et al., In this first post, we’ll analyze self-training , which is a very impactful algorithmic paradigm for semi-supervised learning and domain adaptation. Background: self-training We will first provide a basic overview of self-training algorithms, which are the main focus of this blog post. Chen et al.,

Deep Learning 40

Deep Learning Algorithm Explainability 40

AWS Machine Learning Blog

OCTOBER 17, 2023

billion RMB in 2020 and is expected to reach 810 billion RMB in 2025. Lame cow algorithm: Normalize the anomalies to obtain a score to determine the degree of cow lameness. As a result, we ultimately chose OC-SORT as our tracking algorithm. This requires switching to other algorithms to solve the problem.

Computer Vision 132

Computer Vision Algorithm AI AI 132

ML @ CMU

MARCH 31, 2023

However, while numerous explainable AI (XAI) methods have been developed, XAI has yet to deliver on this promise. The stages of evaluation are adapted from Doshi-Velez and Kim (2017); we introduce an additional stage, use-case-grounded algorithmic evaluations, in a recent Neurips 2022 paper [ 2 ]. Our contributions. Balayan, V.,

ML 98

ML Explainability Algorithm Machine Learning 98

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.

Computer Vision 93

Computer Vision Machine Learning ML Convolutional Neural Networks 93

AWS Machine Learning Blog

MAY 2, 2023

in 2020 as a model where parametric memory is a pre-trained seq2seq model and the non-parametric memory is a dense vector index of Wikipedia, accessed with a pre-trained neural retriever. If you have a large dataset, the SageMaker KNN algorithm may provide you with an effective semantic search. For more details, see the GitHub repo.

LLM 102

LLM Algorithm Machine Learning Natural Language Processing 102

Dlabs.ai

SEPTEMBER 25, 2020

In this article, we’ll focus on this concept: explaining the term and sharing an example of how we’ve used the technology at DLabs.AI. from 2020 to 2027. let’s first explain basic Robotic Process Automation. let’s first explain basic Robotic Process Automation. Happy reading! The RPA market is currently valued at USD 1.1

Automation 52

Automation Auto-classification Robotics Auto-complete 52

Heartbeat

AUGUST 1, 2023

Scale-Invariant Feature Transform (SIFT) This is an algorithm created by David Lowe in 1999. It’s a general algorithm that is known as a feature descriptor. After picking the set of images you desire to use, the algorithm will detect the keypoints of the images and store them in a database. It detects corners.

Computer Vision 52

Computer Vision Deep Learning Neural Network Algorithm 52

Flipboard

FEBRUARY 2, 2023

We then explain the details of the ML methodology and model training procedures. Models were trained and cross-validated on the 2018, 2019, and 2020 seasons and tested on the 2021 season. In this post, we demonstrate how to use Spliced Binned-Pareto distribution implemented in GluonTS to robustly model such fat-tailed distributions.

Machine Learning 123

Machine Learning ML Big Data Data Scientist 123

AI Impacts

JULY 20, 2023

We explain why model evaluation is critical for addressing extreme risks. Survey on intermediate goals in AI governance (Rethink Priorities, Räuker and Aird, March) It seems that a key bottleneck for the field of longtermism-aligned AI governance is limited strategic clarity (see Muehlhauser, 2020 , 2021 ). 10,000X as much).

AI Strategy 100

AI Strategy Neural Network AI AI 100

AWS Machine Learning Blog

AUGUST 14, 2023

Amazon SageMaker JumpStart is a machine learning (ML) hub offering algorithms, models, and ML solutions. Answer: 2021 ### Context: NLP Cloud developed their API by mid-2020 and they added many pre-trained open-source models since then. He focuses on developing scalable machine learning algorithms.

NLP 94

NLP Robotics Prompt Engineer Prompt Engineering 94

AI Impacts

APRIL 7, 2023

Every algorithm for evaluating the solution has some numerical error. Most of the systems we care about are considerably messier than the simple examples we use to explain chaos. Niels Bohr Institute, Copenhagen 2020). There are many ways small uncertainties can arise: Every measuring device has a finite precision. Mainieri, G.

Explainability 130

Explainability Algorithm AI AI 130

Mlearning.ai

JANUARY 17, 2024

Major milestones in the last few years comprised BERT (Google, 2018), GPT-3 (OpenAI, 2020), Dall-E (OpenAI, 2021), Stable Diffusion (Stability AI, LMU Munich, 2022), ChatGPT (OpenAI, 2022). Generative AI models usually have millions of neurons and billions of synapses (aka „ parameters “).

Generative AI 98

Generative AI Prompt Engineer Prompt Engineering Large Language Models 98

Heartbeat

FEBRUARY 27, 2023

Below are some of the most promising use cases for DRL and GANs: DRL: Robotics: DRL algorithms can be applied to teach robots how to carry out particular tasks, including grabbing items or navigating. A significant advancement in DRL has been the introduction of new continuous action space handling algorithms like DDPG and TD3.

Machine Learning 52

Machine Learning Deep Learning Robotics Neural Network 52

Snorkel AI

JANUARY 31, 2023

Seldon is a deployment solution that helps teams serve, monitor, explain, and manage their ML models in production. Modern ML systems include the ability to discover models, monitor drift, explain predictions, and control who has access. Model Management Simply having a model deployed covers the bare minimum of the MLOps lifecycle.

Data Drift 52

Data Drift Explainability Data Scientist AI 52

Snorkel AI

JANUARY 31, 2023

Seldon is a deployment solution that helps teams serve, monitor, explain, and manage their ML models in production. Modern ML systems include the ability to discover models, monitor drift, explain predictions, and control who has access. Model Management Simply having a model deployed covers the bare minimum of the MLOps lifecycle.

Data Drift 52

Data Drift Explainability Data Scientist AI 52

AWS Machine Learning Blog

APRIL 3, 2023

JumpStart is the machine learning (ML) hub of Amazon SageMaker that offers a one-click access to over 350 built-in algorithms; pre-trained models from TensorFlow, PyTorch, Hugging Face, and MXNet; and pre-built solution templates. He focuses on developing scalable machine learning algorithms.

Natural Language Processing 103

Natural Language Processing NLP Prompt Engineer Prompt Engineering 103

Mlearning.ai

MARCH 9, 2023

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., Understanding the robustness of image segmentation algorithms to adversarial attacks is critical for ensuring their reliability and security in practical applications.

Deep Learning 52

Deep Learning Computer Vision Machine Learning Algorithm 52