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SHAP for Binary and Multiclass Target VariablesA guide to the code and interpreting SHAP plots when your model predicts a categorical target variablePhoto by Nika Benedictova on UnsplashSHAP values give the contribution of a model feature to a prediction. For binary target variables, we interpret these values in terms of log odds. For multiclass targets, we use softmax. We will:Discuss these interpretations in more depthGive…

Configuring Nemo-Guardrails Your Way: An Alternative Method for Large Language ModelsPhoto by King's Church International on UnsplashAs advancements in Large Language Models (LLMs) continue to revolutionize various applications, the challenge of ensuring their safe and secure deployment has never been more critical. Enter “guardrails,” a technology designed to mitigate risks and enhance the reliability of these models.In this blog post, we’ll explore the diverse types of guardrails…

AI could help companies connect with customers like never beforeCustomers expect the best experience thanks to artificial intelligence, but they also want to know when AI is being used.

This AI Paper Presents a Study on AIS (Androgen Insensitivity Syndrome) Testing Using Deep Learning ModelsAIS stands for Androgen Insensitivity Syndrome. AIS is a spinal brain problem that affects the younger generation and makes their lives even worse. It causes back pain and can harm the heart and lungs. The very important thing to note about AIS is that it should be noticed in the early stage. It grows even…

Revolutionizing Computer Vision: Advancements, Challenges, and Future DirectionsThere has been an uprise in the use of computer vision making different fields more efficient, effective, and safe. Computer Vision is a cutting-edge interdisciplinary field that empowers machines to understand visual information taken from the world around us. Computer vision does this by mimicking the capabilities of human vision, all the while utilizing advanced…

Amazon Researchers Introduce ‘HandsOff’ Method that Eliminates the Need to Hand-Annotate Synthetic Image DataThe Challenge of Annotating Synthetic Data Using machine learning (ML) models for computer vision tasks heavily relies on labeled training data. However, gathering and annotating this data can take time and effort. Synthetic data has emerged as a feasible solution to this problem, but even generating synthetic data often requires laborious hand annotation by human…

How sure is sure? Incorporating human error into machine learningBy Sarah Collins Human error and uncertainty are concepts that many artificial intelligence systems fail to grasp, particularly in systems where a human provides feedback to a machine learning model. Many of these systems are programmed to assume that humans are always certain and correct, but real-world decision-making includes occasional mistakes and uncertainty. Researchers from…

This AI Research Presents Lucene Integration for Powerful Vector Search with OpenAI EmbeddingsLately, there have been significant strides in applying deep neural networks to the search field in machine learning, with a specific emphasis on representation learning within the bi-encoder architecture. In this framework, various types of content, including queries, passages, and even multimedia, such as images, are transformed into compact and meaningful “embeddings” represented as dense…

Make ChatGPT a Better Software Developer: SoTaNa is an Open-Source AI Assistant for Software DevelopmentHow we do what we do has changed rapidly in recent years. We have started to use virtual assistants for most of the tasks we have and found ourselves in a position where we feel the need to keep delegating our tasks to an AI agent. There is a key that unlocks the power to…

Researchers at NTU Singapore Propose PointHPS: An AI Framework for Accurate Human Pose and Shape Estimation from 3D Point CloudsWith several advancements in the field of Artificial Intelligence, human pose and shape estimation (HPS) has become an increasingly important research area in recent years. With several practical applications, including motion capture, virtual try-on, and mixed reality, recovering 3D human bodies has become a significant challenge. Estimating poses and how the body is arranged, along…

XLang NLP Lab Researchers Propose Lemur: The State-of-the-Art Open Pretrained Large Language Models Balancing Text and Code CapabilitiesIn a world increasingly driven by the intersection of language and technology, the demand for versatile and powerful language models has never been greater. Traditional large language models (LLMs) have excelled in textual comprehension or coding tasks but seldom managed to strike a harmonious balance between the two. This imbalance has left a gap in…

Embracing Neuronal Diversity: A Leap in AI Efficiency and PerformanceThe role of diversity has been a subject of discussion in various fields, from biology to sociology. However, a recent study from North Carolina State University's Nonlinear Artificial Intelligence Laboratory (NAIL) opens an intriguing dimension to this discourse: diversity within artificial intelligence (AI) neural networks. The Power of Self-Reflection: Tuning Neural Networks Internally William Ditto,…

Soft Computing. Volume 27, Issue 20, October 20231) Decision-making problem based on generalized interval-valued bipolar neutrosophic Einstein fuzzy aggregation operatorAuthor(s): A. Fahmi, M. Aslam, R. AhmedPages: 14533 - 145512) Solutions of non-homogeneous system of fuzzy fractional differential equations: a novel approachAuthor(s): V. Padmapriya, M. KaliyappanPages: 14553 - 145693) A customized TOPSIS method to rank the best airlines to fly during COVID-19 pandemic with q-rung…

Researchers from Inception, MBZUAI, and Cerebras Open-Sourced ‘Jais’: The World’s Most Advanced Arabic Large Language ModelLarge language models like GPT-3 and their impact on various aspects of society are a subject of significant interest and debate. Large language models have significantly advanced the field of NLP. They have improved the accuracy of various language-related tasks, including translation, sentiment analysis, summarization, and question-answering. Chatbots and virtual assistants powered by large language…

Efficient Deep Learning: Unleashing the Power of Model CompressionAccelerate model inference speed in productionContinue reading on Towards Data Science »

This AI Paper Introduces the Complexity-Impacted Reasoning Score (CIRS): Evaluating the Role of Code Complexity in Enhancing the Reasoning Abilities of Large Language ModelsLarge language models (LLMs) have become a general-purpose approach to embodied artificial intelligence problem-solving. When agents need to understand the semantic nuances of their environment for efficient control, LLMs’ reasoning skills are crucial in embodied AI. Recent methods, which they refer to as “programs of thought,” use programming languages as an improved prompting system for…

Researchers from the University in Yokohama Propose VirSen1.0: A Virtual Environment for Streamlining the Development of Sensor-Based Human Gesture Recognition SystemsGesture recognition technology faces significant challenges in sensor configuration and placement, data interpretation, and machine learning accuracy. Efficiently setting up sensors to capture nuanced movements, reliably interpreting the resulting data, and ensuring that the machine learning algorithms accurately recognize the intended gestures remain persistent problems. These issues not only hinder optimal performance but also limit…

A Brain-Inspired Learning Algorithm Enables Metaplasticity in Artificial and Spiking Neural NetworksCredit assignment in neural networks for correcting global output mistakes has been determined using many synaptic plasticity rules in natural neural networks. Short-term plasticity, Hebbian learning, and spike-timing-dependent plasticity (STDP) have been the primary focuses of previous attempts to bring biologically relevant plasticity principles into spiking and nonspiking ANNs. STDP goes beyond Hebbian learning by…

Meta AI’s Two New Endeavors for Fairness in Computer Vision: Introducing License for DINOv2 and Releasing FACETIn the ever-evolving field of computer vision, a pressing concern is the imperative to ensure fairness. This narrative illuminates the vast potential residing in AI technology, particularly within computer vision, where it stands as a catalyst for transformative breakthroughs across diverse sectors, from maintaining ecological preservation efforts to facilitating groundbreaking scientific exploration. Yet, it remains…

Top AI Email Assistants (September 2023)Artificial intelligence email assistants have made writing an email quicker and easier. Automatic task completion, message prioritization, and prompt, insightful answers are just how AI email assistants may ease the burden of managing your inbox. As a result, users can direct their attention to the most pressing emails and get more done in less time.…

Meet AnomalyGPT: A Novel IAD Approach Based on Large Vision-Language Models (LVLM) to Detect Industrial AnomaliesOn various Natural Language Processing (NLP) tasks, Large Language Models (LLMs) such as GPT-3.5 and LLaMA have displayed outstanding performance. The capacity of LLMs to interpret visual information has more recently been expanded by cutting-edge techniques like MiniGPT-4, BLIP-2, and PandaGPT by aligning visual aspects with text features, ushering in a huge shift in the…

This AI Research Paper Presents a Comprehensive Survey of Deep Learning for Visual Localization and MappingIf I ask you, “Where are you now?'” or “What do your surroundings look like?” you will immediately be able to answer owing to a unique ability known as multisensory perception in humans that allows you to perceive your motion and your surrounding environment ensuring you have complete spatial awareness. But think as if the…

Entropy based Uncertainty PredictionThis article explores how Entropy can be employed as a tool for uncertainty estimation in image segmentation tasks. We will walk through what Entropy is, and how to implement it with Python.Photo by Michael Dziedzic on UnsplashWhile working at Cambridge University as a Research Scientist in Neuroimaging and AI, I faced the challenge of performing image segmentation…

Is PyTorch’s Nesterov Momentum Implementation Wrong?Momentum helps SGD traverse complex loss landscapes more efficiently. Photo by Maxim Berg on Unsplash.IntroductionIf you look closely at PyTorch’s documentation of SGD, you will find that their implementation of Nesterov momentum has a few differences from the formulation found in the original paper. Most notably, PyTorch’s implementation evaluates the gradient at the current parameters,…

Unlocking the Power of Diversity in Neural Networks: How Adaptive Neurons Outperform Homogeneity in Image Classification and Nonlinear RegressionA neural network is a method in artificial intelligence that teaches computers to process data in a way inspired by the human brain. It uses interconnected nodes or neurons in a layered structure that resembles the human brain. Artificial neurons are arranged into layers to form neural networks, which are used for various tasks such…

Machine Learning’s Public Perception ProblemWhy machine learning literacy for the public needs to be a priority for data science, and what we can do about it.Photo by Andrew Seaman on UnsplashI was listening to a podcast recently with an assortment of intelligent, thoughtful laypeople (whose names I will not share, to be polite) talking about how AI can be used in…

10 Best AI Website Builders (September 2023)The landscape of website building has undergone a radical transformation with the advent of artificial intelligence (AI). Gone are the days when you needed to be proficient in coding or reliant on web designers to build your site. Now, AI-driven platforms can help you construct a compelling online presence in a fraction of the time,…

The Ultimate Guide to Training BERT from Scratch: IntroductionDemystifying BERT: The definition and various applications of the model that changed the NLP landscape.Continue reading on Towards Data Science »

Top AI-Based Art Inpainting ToolsArtificial intelligence picture inpainting is a computer vision approach for restoring images that have been damaged or missing details. In addition to fixing outdated or damaged photos, it may also be used to crop out distracting backgrounds or even create entirely new images. Several artificial intelligence (AI) picture inpainting programs are already on the market,…

Microsoft Researchers Propose Open-Vocabulary Responsible Visual Synthesis (ORES) with the Two-Stage Intervention FrameworkVisual synthesis models may produce increasingly realistic visuals thanks to the advancement of large-scale model training. Responsible AI has grown more crucial due to the increased potential for using synthesized pictures, particularly to eliminate specific visual elements during syntheses, such as racism, sexual discrimination, and nudity. But for two fundamental reasons, responsible visual synthesis is…

AI2 Researchers Introduce Satlas: A New AI Platform for Exploring Global Geospatial Data Generated by Artificial Intelligence from Satellite ImageryIn a world where timely and accurate geospatial data is crucial for addressing many global challenges, the lack of comprehensive and up-to-date information has been a persistent problem. Manual curation of geospatial data, especially in the realm of renewable energy infrastructure and natural resource monitoring, involves a thorough process of aggregating, cleaning, and correcting datasets…

Revolutionizing Speech Restoration: Stanford-Led Research Unveils High-Performance Neuroprosthesis for Unconstrained Communication”Speech brain-computer interfaces (BCIs) are a cutting-edge technological advancement with promising applications for rehabilitating individuals who lost the ability to communicate due to a disability. Decoding brain processes to enable communication of unrestricted phrases from a huge lexicon is still in its infancy, although early investigations have shown promise. As a means of filling this…

Natural Language Processing For Absolute BeginnersSolving complex NLP tasks in 10 lines of Python codeContinue reading on Towards Data Science »

Meet RecMind: An Autonomous Recommender Agent Driven by Large Language Models Technology that Combines Reasoning, Action, and Memory for Various Recommendation TasksWith the increase in popularity of Artificial Intelligence and Deep Learning, almost every other application is utilizing the capabilities of AI to get things done. DNNs or deep neural networks have been essential in modernizing Recommender Systems. A recommender system is an essential part of numerous online platforms, such as search engines, e-commerce websites, social…

How to Ace the Data Science Bootcamp: A Complete GuideA full guide on how to prepare for a bootcamp, successfully complete the course, and act afterwardHow a Neural Network Sees a girl in a Data Science Bootcamp (image generated with Kandinsky 2.2 by the author)I’ve graduated from offline bootcamp in May 2021. Now I have been working in IT for almost 2 years. Moreover, I…

Deci Introduces DeciCoder: An Open-Source 1B-Parameter Large Language Model For Code GenerationIn the fast-paced world of AI, efficient code generation is a challenge that can’t be overlooked. With the advent of increasingly complex models, the demand for accurate code generation has surged, but so have concerns about energy consumption and operational costs. Addressing this efficiency gap head-on, Deci, a pioneering AI company, introduces DeciCoder, a 1-billion-parameter…

30+ AI Tools For Startups (September 2023)Workplace creativity, analysis, and decision-making are all being revolutionized by AI. Today, artificial intelligence capabilities present a tremendous opportunity for businesses to hasten expansion and better control internal processes. Artificial intelligence applications are vast, ranging from automation and predictive analytics to personalization and content development. Here is a rundown of the best artificial intelligence tools…

University of Zurich Researchers Introduce Swift: An Autonomous Vision-based Drone that can Beat human World Champions in Several Fair Head-to-Head RacesFirst-person view (FPV) drone racing is an exhilarating and rapidly growing sport where pilots control racing drones from a first-person perspective using specialized FPV goggles. The drones have powerful motors, lightweight frames, and high-quality cameras for low-latency video transmission in this sport. Pilots wear FPV goggles that provide a live video feed from the drone’s…

Tidying Up the Framework of Dataset Shifts: The ExampleHow the conditional probability changes as a function of the three probability elementsImage by authorI recently talked about the causes of model performance degradation, meaning when their prediction quality drops with respect to the moment we trained and deployed our models. In this other post, I proposed a new way of thinking about the causes of…

X’s privacy policy confirms it will use public data to train AI modelsX’s recently updated privacy policy informed its users it would now collect biometric data as well as users’ job and education history, Bloomberg spotted earlier this week. But it appears that’s not the only thing that X plans to do with user data. According to an update to another section of the policy, the company…

Google AI Introduces WeatherBench 2: A Machine Learning Framework for Evaluating and Comparing Various Weather Forecasting ModelsMachine learning (ML) has been used increasingly in weather forecasting in recent years. Now that ML models can compete with operational physics-based models in terms of accuracy, there is hope that this progress may soon make it possible to enhance the precision of weather forecasts around the world. Open and reproducible evaluations of novel methods…

Solving a Leetcode problem using Reinforcement learningSolving a Leetcode Problem Using Reinforcement learningA practical introduction to reinforcement learningRecently, I came across a question on leetcode : Shortest Path in a Grid with Obstacles Elimination. The Shortest Path in a Grid with Obstacles Elimination problem involves finding the shortest path from a starting cell to a target cell in a 2D grid containing…

Fast-tracking fusion energy’s arrival with AI and accessibilityMIT Plasma Science and Fusion Center will receive DoE support to improve access to fusion data and increase workforce diversity.

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Simplify medical image classification using Amazon SageMaker CanvasAnalyzing medical images plays a crucial role in diagnosing and treating diseases. The ability to automate this process using machine learning (ML) techniques allows healthcare professionals to more quickly diagnose certain cancers, coronary diseases, and ophthalmologic conditions. However, one of the key challenges faced by clinicians and researchers in this field is the time-consuming and…

Scalable spherical CNNs for scientific applicationsPosted by Carlos Esteves and Ameesh Makadia, Research Scientists, Google Research, Athena Team Typical deep learning models for computer vision, like convolutional neural networks (CNNs) and vision transformers (ViT), process signals assuming planar (flat) spaces. For example, digital images are represented as a grid of pixels on a plane. However, this type of data makes…

Code Llama code generation models from Meta are now available via Amazon SageMaker JumpStartToday, we are excited to announce Code Llama foundation models, developed by Meta, are available for customers through Amazon SageMaker JumpStart to deploy with one click for running inference. Code Llama is a state-of-the-art large language model (LLM) capable of generating code and natural language about code from both code and natural language prompts. Code…

Build an end-to-end MLOps pipeline for visual quality inspection at the edge – Part 1A successful deployment of a machine learning (ML) model in a production environment heavily relies on an end-to-end ML pipeline. Although developing such a pipeline can be challenging, it becomes even more complex when dealing with an edge ML use case. Machine learning at the edge is a concept that brings the capability of running…

Build an end-to-end MLOps pipeline for visual quality inspection at the edge – Part 2In Part 1 of this series, we drafted an architecture for an end-to-end MLOps pipeline for a visual quality inspection use case at the edge. It is architected to automate the entire machine learning (ML) process, from data labeling to model training and deployment at the edge. The focus on managed and serverless services reduces…

Google at ICCV 2023Posted by Shaina Mehta, Program Manager, Google Google is proud to be a Platinum Sponsor of the International Conference on Computer Vision (ICCV 2023), a premier annual conference, which is being held this week in Paris, France. As a leader in computer vision research, Google has a strong presence at this year’s conference with 60…

When Does Optimizing a Proper Loss Yield Calibration?Optimizing proper loss functions is popularly believed to yield predictors with good calibration properties; the intuition being that for such losses, the global optimum is to predict the ground-truth probabilities, which is indeed calibrated. However, typical machine learning models are trained to approximately minimize loss over restricted families of predictors, that are unlikely to contain…

Build a crop segmentation machine learning model with Planet data and Amazon SageMaker geospatial capabilitiesIn this analysis, we use a K-nearest neighbors (KNN) model to conduct crop segmentation, and we compare these results with ground truth imagery on an agricultural region. Our results reveal that the classification from the KNN model is more accurately representative of the state of the current crop field in 2017 than the ground truth…

Accenture creates a Knowledge Assist solution using generative AI services on AWSThis post is co-written with Ilan Geller and Shuyu Yang from Accenture. Enterprises today face major challenges when it comes to using their information and knowledge bases for both internal and external business operations. With constantly evolving operations, processes, policies, and compliance requirements, it can be extremely difficult for employees and customers to stay up…

Re-weighted gradient descent via distributionally robust optimizationRamnath Kumar, Pre-Doctoral Researcher, and Arun Sai Suggala, Research Scientist, Google Research Deep neural networks (DNNs) have become essential for solving a wide range of tasks, from standard supervised learning (image classification using ViT) to meta-learning. The most commonly-used paradigm for learning DNNs is empirical risk minimization (ERM), which aims to identify a network that…

Speed up your time series forecasting by up to 50 percent with Amazon SageMaker Canvas UI and AutoML APIsWe’re excited to announce that Amazon SageMaker Canvas now offers a quicker and more user-friendly way to create machine learning models for time-series forecasting. SageMaker Canvas is a visual point-and-click service that enables business analysts to generate accurate machine learning (ML) models without requiring any machine learning experience or having to write a single line of code. SageMaker…

Beyond forecasting: The delicate balance of serving customers and growing your businessCompanies use time series forecasting to make core planning decisions that help them navigate through uncertain futures. This post is meant to address supply chain stakeholders, who share a common need of determining how many finished goods are needed over a mixed variety of planning time horizons. In addition to planning how many units of…

Announcing New Tools to Help Every Business Embrace Generative AIFrom startups to enterprises, organizations of all sizes are getting started with generative AI. They want to capitalize on generative AI and translate the momentum from betas, prototypes, and demos into real-world productivity gains and innovations. But what do organizations need to bring generative AI into the enterprise and make it real? When we talk…

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Our Take on the Latest Posts

Gotta watch your back, AI is here

May 12, 2023
ChatGPT and Generative AI: Our Guide to 2023’s Most Talked-About Technology

May 12, 2023

Our Take on the Latest Posts

Gotta watch your back, AI is here

ChatGPT and Generative AI: Our Guide to 2023’s Most Talked-About Technology