Flipboard

FEBRUARY 4, 2025

If, instead, you step back and view these companies with a 21st century mindset, you realize that a large part of the work of these companies delivering search results, news and information, social network status updates, and relevant products for purchase is done by software programs and algorithms.

Software Development 182

Software Development Automation Software Engineer Explainability 182

Unite.AI

NOVEMBER 29, 2023

Looking back at the recent past, the 2016 US presidential election result makes us explore what influenced voters' decisions. AI watchdogs employ state-of-the-art technologies, particularly machine learning and deep learning algorithms, to combat the ever-increasing amount of election-related false information.

Responsible AI 195

Responsible AI AI AI Algorithm 195

Unite.AI

JULY 30, 2024

He has more than 25 years of experience in algorithm development, AI and machine learning from academia as well as serving in an elite unit in the Israeli military and at several tech companies. Since 2016, Ibex has led the way in AI-powered diagnostics for pathology. Our approach is that pathologists essentially train the machine.

Machine Learning 147

Machine Learning Artificial Intelligence Artificial Intelligence Algorithm 147

AWS Machine Learning Blog

APRIL 7, 2025

In this demonstration, the model is prompted with two image URLs and tasked with describing each image and explaining their relationship, showcasing its capacity to synthesize information across several visual inputs. Lets test this below by passing in the URLs of the following images in the payload. billion to a projected $574.78

Machine Learning 81

Machine Learning Large Language Models Python Automation 81

AWS Machine Learning Blog

FEBRUARY 21, 2025

There are various techniques of preference alignment, including proximal policy optimization (PPO), direct preference optimization (DPO), odds ratio policy optimization (ORPO), group relative policy optimization (GRPO), and other algorithms, that can be used in this process. Set up a SageMaker notebook instance.

LLM 80

LLM AI AI Data Scientist 80

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?

Machine Learning 52

Machine Learning Explainability Deep Learning Explainable AI 52

TheSequence

MARCH 9, 2025

These pioneers have laid the conceptual and algorithmic foundations of RL, shaping the future of artificial intelligence and decision-making systems. One of RL's most notable early successes was demonstrated by Google DeepMind's AlphaGo, which defeated world-class human Go players in 2016 and 2017. Barto and Richard S.

LLM 52

LLM Robotics Artificial Intelligence Artificial Intelligence 52

Unite.AI

JULY 8, 2024

Prior to Zingtree, Brandon led Product, User Experience and Analytics at SportsEngine, a B2B and B2B2C SaaS company which was acquired by NBC Sports in 2016. Could you explain the core function of Zingtree's AI-enabled support automation platform and how it differentiates itself from other solutions in the market?

Automation 130

Automation Chatbots Algorithm Large Language Models 130

Unite.AI

AUGUST 5, 2024

I received my masters in Civil/Environmental Engineering from Stanford University in 2016. Can you explain the process of training AI models with field-tested data from vital infrastructure sites? We use three main different types of algorithms: image clustering, segmentation, and anomaly detection.

Machine Learning 147

Machine Learning Artificial Intelligence Artificial Intelligence Computer Vision 147

AI Impacts

DECEMBER 13, 2023

For AI, this is the distinction between algorithmic progress and hardware progress. Figure 3: Bandwidth-distance product in fiber optics alone, 9 from Agrawal, 2016. 10 This figure comes from a book chapter (Agrawal, 2016) which also explains the history. 11 The result is again a combination of S-curves. AI Impacts Wiki.

Explainability 147

Explainability AI AI AI Developer 147

Viso.ai

NOVEMBER 27, 2024

YOLO (You Only Look Once) is a family of real-time object detection machine-learning algorithms. Multiple machine-learning algorithms are used for object detection, one of which is convolutional neural networks (CNNs). Improved Explainability : Making the model’s decision-making process more transparent.

Explainability 52

Explainability Convolutional Neural Networks Neural Network Computer Vision 52

Unite.AI

JUNE 17, 2024

However, the real turning point for me was around 2015-2016, when AI started making headline news with breakthroughs like AlphaGo defeating the world champion in the complex game of Go. Algorithms can analyze market data, news sentiment, and social media trends to predict stock prices and optimize portfolio allocation.

Automation 147

Automation Artificial Intelligence Artificial Intelligence Generative AI 147

Unite.AI

AUGUST 1, 2024

Can you explain the key features and benefits of Pimloc's Secure Redact privacy platform? These deep learning algorithms are trained on domain-specific videos from sources like CCTV, body-worn cameras, and road survey footage. Pimloc’s AI models accurately detect and redact PII even under challenging conditions.

Machine Learning 147

Machine Learning Deep Learning Automation Computer Vision 147

Viso.ai

MARCH 11, 2024

This was done by using a region proposal algorithm to generate potential bounding boxes (regions) in the image. The YOLO algorithm works by predicting three different features: Grid Division: YOLO divides the input image into a grid of cells. Timeline of YOLO Models What is YOLOX? How Does YOLOX Work?

Explainability 52

Explainability Convolutional Neural Networks Neural Network Computer Vision 52

Unite.AI

FEBRUARY 16, 2024

For example, see Face-to-Face Interaction with Pedagogical Agents, Twenty Years Later , a 2016 article that overviews the field and cites a lot of the relevant material. Children download the App and convince parents to pay for a subscription, explaining that Buddy is a teacher.

Natural Language Processing 173

Natural Language Processing UX Design AI AI 173

Pickl AI

APRIL 8, 2024

This blog explores 13 major AI blunders, highlighting issues like algorithmic bias, lack of transparency, and job displacement. From the moment we wake up to the personalized recommendations on our phones to the algorithms powering facial recognition software, AI is constantly shaping our world.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Algorithm AI 52

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

PyImageSearch

NOVEMBER 13, 2023

One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al. Since then, the R-CNN algorithm has gone through numerous iterations, improving the algorithm with each new publication and outperforming traditional object detection algorithms (e.g.,

Convolutional Neural Networks 118

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 118

Topbots

JUNE 22, 2023

Also, since at least 2018, the American agency DARPA has delved into the significance of bringing explainability to AI decisions. Outstandingly, ChatPGT presents such a capacity: it can explain its decisions. Outperforming algorithmic trading reinforcement learning systems: A supervised approach to the cryptocurrency market.

Machine Learning 111

Machine Learning ChatGPT Natural Language Processing Categorization 111

TransOrg Analytics

MAY 27, 2024

This article explores the transformative impact of LLM chatbots compared to traditional chatbots and explains how TranOrg provided an LLM chatbot for an Airline company. million US dollars in 2016 and is expected to grow to 1250 million US dollars in 2025. that can understand images and explain things.

LLM 52

LLM Chatbots Continuous Learning Natural Language Processing 52

Marktechpost

FEBRUARY 17, 2025

The study’s bibliometric analysis revealed a steady increase in AI safety research since 2016, driven by advancements in deep learning. Research methods include applied algorithms, simulated agents, analysis frameworks, and mechanistic interpretability.

Categorization 47

Categorization Deep Learning Metadata AI 47

ML Review

JUNE 4, 2018

These ideas also move in step with the explainability of results. Finally, one can use a sentence similarity evaluation metric to evaluate the algorithm. One such evaluation metric is the Bilingual Evaluation Understudy algorithm, or BLEU score. Source : Britz (2016)[ 62 ] CNNs can encode abstract features from images.

Neural Network 52

Neural Network Convolutional Neural Networks Computer Vision Deep Learning 52

AWS Machine Learning Blog

JANUARY 17, 2024

He retired from EPFL in December 2016.nnIn nnIn 1996, Moret founded the ACM Journal of Experimental Algorithmics, and he remained editor in chief of the journal until 2003. About the Authors Xin Huang is a Senior Applied Scientist for Amazon SageMaker JumpStart and Amazon SageMaker built-in algorithms.

Auto-complete 124

Auto-complete Python Machine Learning Deep Learning 124

AWS Machine Learning Blog

JULY 13, 2023

Another way can be to use an AllReduce algorithm. For example, in the ring-allreduce algorithm, each node communicates with only two of its neighboring nodes, thereby reducing the overall data transfers. Train a binary classification model using the SageMaker built-in XGBoost algorithm. alpha – L1 regularization term on weights.

Algorithm 80

Algorithm Deep Learning Neural Network Machine Learning 80

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

Heartbeat

AUGUST 23, 2023

Consider a scenario where legal practitioners are armed with clever algorithms capable of analyzing, comprehending, and extracting key insights from massive collections of legal papers. Algorithms can automatically detect and extract key items. But what if there was a technique to quickly and accurately solve this language puzzle?

NLP 52

NLP Natural Language Processing Algorithm Categorization 52

Pickl AI

JULY 24, 2024

Turing proposed the concept of a “universal machine,” capable of simulating any algorithmic process. The development of LISP by John McCarthy became the programming language of choice for AI research, enabling the creation of more sophisticated algorithms. Simon, demonstrated the ability to prove mathematical theorems.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Natural Language Processing Neural Network 52

ML Review

MAY 3, 2018

2016) — “ LipNet: End-to-End Sentence-level Lipreading.” [17] 17] “ LipNet ” introduces the first approach for an end-to-end lip reading algorithm at sentence level. 27] LipNet also makes use of an additional algorithm typically used in speech recognition systems — a Connectionist Temporal Classification (CTC) output.

Neural Network 52

Neural Network Computer Vision Deep Learning NLP 52

AWS Machine Learning Blog

APRIL 18, 2023

To make things easy, these three inputs depend solely on the model name, version (for a list of the available models, see Built-in Algorithms with pre-trained Model Table ), and the type of instance you want to train on. learning_rate – Controls the step size or learning rate of the optimization algorithm during training.

Large Language Models 78

Large Language Models NLP LLM Deep Learning 78

Snorkel AI

MARCH 1, 2023

It is based on GPT and uses machine learning algorithms to generate code suggestions as developers write. This can make it challenging for businesses to explain or justify their decisions to customers or regulators. Microsoft Microsoft launched its Language Understanding Intelligent Service in 2016. What are foundation models?

BERT 83

BERT Natural Language Processing Large Language Models Neural Network 83

Heartbeat

FEBRUARY 2, 2024

The significance of VQA extends beyond traditional computer vision tasks, requiring algorithms to exhibit a broader understanding of context, semantics, and reasoning. It's remarkable diversity and scale position it as a cornerstone for evaluating and benchmarking VQA algorithms.

Computer Vision 52

Computer Vision Natural Language Processing Artificial Intelligence Artificial Intelligence 52

Viso.ai

JULY 17, 2024

Output from Neural Style Transfer – source Neural Style Transfer Explained Neural Style Transfer follows a simple process that involves: Three images, the image from which the style is copied, the content image, and a starting image that is just random noise. With deep learning, the results were impressively good. Gatys et al.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

TheSequence

DECEMBER 13, 2023

My path to working in AI is somewhat unconventional and began when I was wrapping up a postdoc in theoretical particle physics around 2016. Your background, current role and how did you get started in AI? Why another Transformers book, and what sets this one apart?

LLM 64

LLM Natural Language Processing Machine Learning Deep Learning 64

deepsense.ai

APRIL 16, 2023

First, we will explain the MLP block. Source: [ 5 ] It runs GEMM with query ((W^Q)), key ((W^K)), and value weights ((W^V)) according to the previously explained partitioning in parallel. 2016 ), only the activations at the boundaries of each partition are saved and shared between workers during training. billion parameters.

Large Language Models 52

Large Language Models Neural Network Deep Learning Explainability 52

Dlabs.ai

AUGUST 10, 2020

In simple terms, intent detection is the process of algorithmically identifying user intent from a given statement. One of the first widely discussed chatbots was the one deployed by SkyScanner in 2016. Intent detection – what is it? That’s a lot of words to describe a rather simple process, so let’s take a look at an example.

Natural Language Processing 52

Natural Language Processing Chatbots Neural Network Machine Learning 52

John Snow Labs

MAY 23, 2023

This is because NLP technology enables the VQA algorithm to not only understand the question posed to it about the input image, but also to generate an answer in a language that the user (asking the question) can easily understand. This explains why many practical applications have been discovered for VQA in just the last half decade.

Natural Language Processing 40

Natural Language Processing Deep Learning NLP Convolutional Neural Networks 40

Heartbeat

MAY 11, 2023

The first version of YOLO was introduced in 2016 and changed how object detection was performed by treating object detection as a single regression problem. ✨ The algorithm for selecting layers in the model quantizes certain parts to minimize loss of information while ensuring a balance between latency and accuracy.

Deep Learning 75

Deep Learning Computer Vision Data Scientist ML 75