IBM Journey to AI blog

OCTOBER 16, 2023

In other words, instead of training numerous models on labeled, task-specific data, it’s now possible to pre-train one big model built on a transformer and then, with additional fine-tuning, reuse it as needed. Foundation models offer a breakthrough in AI capabilities to enable scalable and efficient deployment across various domains.

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NVIDIA

MARCH 1, 2024

Artificial Intelligence Safety Institute Consortium, or AISIC, to help create tools and standards for responsible AI development and deployment. As a consortium member, NVIDIA will promote trustworthy AI by leveraging best practices for implementing AI model transparency.

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Google Research AI blog

MARCH 6, 2023

In “ Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages ”, we demonstrate that utilizing a large unlabeled multilingual dataset to pre-train the encoder of the model and fine-tuning on a smaller set of labeled data enables us to recognize under-represented languages. A sample of the languages that USM supports.

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ODSC - Open Data Science

MARCH 8, 2024

Bench IQ, a Toronto-based startup, has unveiled an AI platform that promises to change how lawyers prepare for court. Source ) In a blog post released today, OpenAI fired back at Elon Musk’s lawsuit and moved to dismiss his claims about the company’s motives. Blogs or News to Share? Schedule Now Live!

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Artificial Intelligence Artificial Intelligence Large Language Models AI 52

Google Research AI blog

FEBRUARY 7, 2023

In such a setting, a learner can sample examples one at a time, accessing both the context and true label, but in order to limit overhead costs, is only able to update its state (i.e., Google Research, 2022 & beyond This was the fourth blog post in the “Google Research, 2022 & Beyond” series.

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ODSC - Open Data Science

MARCH 24, 2023

Why the Best Time to Learn Python is Right Now In this blog, we will explore five reasons why Python has become the most popular programming language and why it is worth considering for your next project, regardless of your area of expertise. Register by Friday for 50% off.

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Data Ingestion Machine Learning Data Science NLP 52

Towards AI

AUGUST 22, 2023

Gemini is still in training, but it’s already exhibiting multimodal capabilities never before seen in prior models.” — Google CEO blog, May-23. This approach aims to relieve humans of the burden involved, thereby enabling more uniform labeling of content and expediting feedback loops.

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John Snow Labs

OCTOBER 19, 2023

Imagine asking your AI assistant about a contentious political issue, and it effortlessly mirrors your beliefs, regardless of the facts. It’s a phenomenon called sycophancy , and it’s a thorn in the side of AI development. But fret not, for this blog post unveils a powerful antidote to this frustrating issue. Sound familiar?

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IBM Journey to AI blog

DECEMBER 20, 2023

Supervised machine learning Supervised machine learning is a type of machine learning where the model is trained on a labeled dataset (i.e., Classification algorithms —predict categorical output variables (e.g., “junk” or “not junk”) by labeling pieces of input data. Explore the watsonx.ai

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John Snow Labs

SEPTEMBER 4, 2023

In this blog post, we will be testing the robustness of the NERPipeline model, which is good in the f1 score, and evaluating its performance. The process involves extracting labels and corresponding values from an existing dataset and then replacing those values with the provided templates using the labels from the dataset.

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AWS Machine Learning Blog

MAY 14, 2024

The entire conversation in this use case, starting with generative AI and then bringing in human agents who take over, is logged so that the interaction can be used as part of the knowledge base. Together with RLHF, near-real-time human-in-the-loop methods enable the development of responsible and effective generative AI applications.

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John Snow Labs

NOVEMBER 9, 2023

The AI and language processing world is always changing, with new models and tricks popping up all the time. In this blog post, we take on this challenge by enhancing the QA evaluation capabilities using LangTest library. We need to make sure our testing methods are as cutting-edge as the tech itself.

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Large Language Models OpenAI LLM Responsible AI 52

John Snow Labs

SEPTEMBER 4, 2023

In this blog, we’ll dive into LangTest , a way to go beyond just accuracy and explore how well Named Entity Recognition models can handle the twists and turns of real language out there. The primary goal of Named Entity Recognition is to locate and label these named entities in a given text.

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NLP Natural Language Processing Python Categorization 52

John Snow Labs

AUGUST 30, 2023

In this blog post, we will explore the evaluation of robustness and bias in healthcare Named Entity Recognition (NER) models. pipe_labels['ner'], seven_colours): col_dict[label] = colour options = {'ents': med7.pipe_labels['ner'],

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AWS Machine Learning Blog

MAY 13, 2024

In part 1 of this blog series, we discussed how a large language model (LLM) available on Amazon SageMaker JumpStart can be fine-tuned for the task of radiology report impression generation. Amazon Bedrock also comes with a broad set of capabilities required to build generative AI applications with security, privacy, and responsible AI.

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AWS Machine Learning Blog

AUGUST 11, 2023

The framework works by posing the sequence to be classified as an NLI premise and constructs a hypothesis from each candidate label. The probabilities for entailment and contradiction are then converted to label probabilities. Premise Label Hypothesis A man inspects the uniform of a figure in some East Asian country.

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The MLOps Blog

JUNE 27, 2023

This includes features for data labeling, data versioning, data augmentation, and integration with popular data storage systems. Dataset labeling and annotation Dataset labeling and annotation tools form a critical component of machine learning (ML) systems, enabling you to prepare high-quality training data for their models.

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ODSC - Open Data Science

JANUARY 25, 2023

For now, this public registry contains reusable components that make it easier to work with Responsible AI, but new capabilities will continuously be added in the future. She loves to share her knowledge with others through her Azure ML and machine learning blog.

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AssemblyAI

MAY 23, 2023

The widespread use of ChatGPT has led to millions embracing Conversational AI tools in their daily routines. " These models are trained using self-supervised learning , a technique that utilizes the data's inherent structure to generate labels for training. Learn more about it in our dedicated blog series on Generative AI.

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Bugra Akyildiz

MARCH 9, 2024

A new Responsible Generative AI Toolkit provides guidance and essential tools for creating safer AI applications with Gemma. As far as I know, no other GenAI development is focusing the responsible AI aspect of these models. Google wrote a blog post on a new visual encoder for their video understanding.

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AWS Machine Learning Blog

NOVEMBER 29, 2023

Since launching in June 2023, the AWS Generative AI Innovation Center team of strategists, data scientists, machine learning (ML) engineers, and solutions architects have worked with hundreds of customers worldwide, and helped them ideate, prioritize, and build bespoke solutions that harness the power of generative AI.

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Google Research AI blog

FEBRUARY 28, 2023

We also support Responsible AI projects directly for other organizations — including our commitment of $3M to fund the new INSAIT research center based in Bulgaria. Open Images V7 Open Images V7 expands the Open Images dataset with new point-level label annotations, which provide localization information for 5.8k

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Google Research AI blog

MAY 25, 2023

Scene Semantics API uses DeepLab-based semantic segmentation model to provide accurate pixel-wise labels in a scene outdoors. Chirp is able to cover such a wide variety of languages by leveraging self-supervised learning on unlabeled multilingual dataset with fine-tuning on a smaller set of labeled data.

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Flipboard

MARCH 23, 2023

But Transformers have some other important advantages: Transformers don’t require training data to be labeled; that is, you don’t need metadata that specifies what each sentence in the training data means. When you’re training an image model, a picture of a dog or a cat needs to come with a label that says “dog” or “cat.”

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AWS Machine Learning Blog

MARCH 4, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies, such as AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

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AWS Machine Learning Blog

MAY 7, 2024

The solution runs Amazon Rekognition APIs for label detection , text detection, celebrity detection , and face detection on videos. The current architecture consists of three components: Metadata generation – This component generates metadata from a video archive, processes it, and creates embeddings for search indexing.

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AWS Machine Learning Blog

FEBRUARY 27, 2023

In this blog we show you how to automatically tune a ML model with Amazon SageMaker AMT for both accuracy and fairness objectives by creating a single combined metric. Here, we use the absolute value of Difference in Positive Proportions in Predicted Labels ( DPPL ) from SageMaker Clarify. For example, if 4.5%

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AWS Machine Learning Blog

MARCH 14, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

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AWS Machine Learning Blog

OCTOBER 17, 2023

Agents also label the machine-generated response with their feedback (for example, positive or negative). In summary, we saw how Amazon Pharmacy is using generative AI and AWS to improve customer care while prioritizing responsible AI principles and practices.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

AIM340-R (LVL 300) | Customize your FMs securely to deliver differentiated experiences Wednesday November 29 | 6:00 PM – 7:00 PM (PST) Foundation model customizations help you build differentiated generative AI applications using your own data. It’s easy to securely customize models in Amazon Bedrock. Reserve your seat now!

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ML Generative AI Prompt Engineer Prompt Engineering 114

Google Research AI blog

DECEMBER 6, 2022

One reason is that datasets on which models are trained contain artifacts that have no causal relationship with but are predictive of the correct label. Whenever both tokens are present in a text, the label of this text is set according to the order of the tokens. How can that be?

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BERT Neural Network Software Engineer NLP 52

Google Research AI blog

MAY 15, 2023

Last year, in a step toward more inclusive computer vision systems, Google's Responsible AI and Human-Centered Technology team in Research partnered with Dr. Ellis Monk to openly release the Monk Skin Tone (MST) Scale, a skin tone scale that captures a broad spectrum of skin tones.

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AWS Machine Learning Blog

FEBRUARY 8, 2024

At the forefront of this evolution sits Amazon Bedrock , a fully managed service that makes high-performing foundation models (FMs) from Amazon and other leading AI companies available through an API. With Amazon Bedrock, you can build and scale generative AI applications with security, privacy, and responsible AI.

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AWS Machine Learning Blog

JANUARY 4, 2024

Both approaches could be considered and selected based on the right set of requirements: Fine-tuning – The baseline model is pre-trained on a large general text corpus and then can use instruction-based fine-tuning , which uses labeled examples to improve the performance of a pre-trained foundation model on text-SQL.

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Viso.ai

DECEMBER 20, 2023

In this blog article, we’ll explore MindSpore in-depth: Understanding the Architecture Reviewing Optimization Techniques Exploring Adaptability Ease of development Upsides and Commercial Risks About us : Viso Suite is the most powerful end-to-end computer vision platform. It accelerates AI research and prototype development.

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Google Research AI blog

JANUARY 18, 2023

Posted by Jeff Dean, Senior Fellow and SVP of Google Research, on behalf of the Google Research community Today we kick off a series of blog posts about exciting new developments from Google Research. The neural network perceives an image, and generates a sequence of tokens for each object, which correspond to bounding boxes and class labels.

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Snorkel AI

MARCH 2, 2023

In media and gaming: designing game storylines, scripts, auto-generated blogs, articles and tweets, and grammar corrections and text formatting. The responsible AI measures pertaining to safety and misuse and robustness are elements that need to be additionally taken into consideration. Over time you monitor its drift.

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