Robot Writers AI

FEBRUARY 11, 2024

From the Department of Love, AI Style: A Russian man has used AI writing to whisper sweet nothings to 5,000+ potential lovers — and find himself a bride. “To do this, the neural network re-communicated with 5,239 other girls — whom it eliminated as unnecessary and left only one.”

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ODSC - Open Data Science

JANUARY 11, 2024

Getting Started with AI in High-Risk Industries, How to Become a Data Engineer, and Query-Driven Data Modeling How To Get Started With Building AI in High-Risk Industries This guide will get you started building AI in your organization with ease, axing unnecessary jargon and fluff, so you can start today.

Data Science 52

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AWS Machine Learning Blog

NOVEMBER 22, 2023

Similar to the rest of the industry, the advancements of accelerated hardware have allowed Amazon teams to pursue model architectures using neural networks and deep learning (DL). PyTorch XLA converts PyTorch’s eager mode to lazy mode graph-based implementation. To use accelerators, you need a software layer to support them.

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LLM Software Engineer Auto-complete Neural Network 93

IBM Journey to AI blog

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data. What is text mining?

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Pickl AI

AUGUST 1, 2023

It is the process of deriving valuable patterns, trends, and insights from unstructured textual data. By analyzing text data, businesses can gain valuable insights into customer sentiments, emerging trends, market preferences, and competitor analysis. Text mining is also known as text analytics or Natural Language Processing (NLP).

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Data Analysis Python Categorization Data Mining 52

Pickl AI

MAY 30, 2023

Networking Opportunities: With professional short-term certification program, you get the opportunity to be associated with like-minded individuals and collaborate with industry specialists. It allows you to network with different experts in the industry and expands you capabilities to communicate with them.

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Data Mining Data Science Deep Learning Machine Learning 52

Snorkel AI

JULY 6, 2023

Nyla Worker, product manager at NVIDIA gave a presentation entitled “Leveraging Synthetic Data to Train Perception Models Using NVIDIA Omniverse Replicator” at Snorkel AI’s The Future of Data-Centric AI virtual conference in August 2022. You can read more about that in blogs, but overall, this can be used in multiple industries.

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AI AI Neural Network Deep Learning 59

Snorkel AI

JULY 6, 2023

Nyla Worker, product manager at NVIDIA gave a presentation entitled “Leveraging Synthetic Data to Train Perception Models Using NVIDIA Omniverse Replicator” at Snorkel AI’s The Future of Data-Centric AI virtual conference in August 2022. You can read more about that in blogs, but overall, this can be used in multiple industries.

AI 59

AI AI Neural Network Deep Learning 59

ML Review

MARCH 5, 2019

Different lenses to see through AI; motivations and introduction to our web app At MTank , we work towards two goals. (1) 1) Model and distil knowledge within AI. (2) Part 1: A bird’s eye view of AI research Part 2: Distilling by Embedding What is this and why did you do it? Why, you ask?

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AssemblyAI

MAY 3, 2023

In the grand tapestry of modern artificial intelligence, how do we ensure that the threads we weave when designing powerful AI systems align with the intricate patterns of human values? This question lies at the heart of AI alignment , a field that seeks to harmonize the actions of AI systems with our own goals and interests.

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Large Language Models Neural Network LLM Chatbots 363

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.

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Explainability Machine Learning Deep Learning Explainable AI 52

AssemblyAI

JUNE 27, 2023

Over the past decade, we've witnessed significant advancements in AI-powered audio generation techniques, including music and speech synthesis. This trend has recently begun to shift. This blog post is part of a series on generative AI.

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AssemblyAI

AUGUST 15, 2023

The history of asynchronous I/O in Python** In the late 1990s and early 2000s, the Python standard library included modules for asynchronous I/O and networking. The decline in NPS has slowed, though more data is needed to determine if it is an actual trend. However, over time these modules became outdated.

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Python Large Language Models Neural Network Algorithm 130

Mlearning.ai

FEBRUARY 2, 2023

In this blog, we will be solving the FrozenLake v1 environment problem for 10*10 state space through the use of Q-Learning and Deep Q-Learning. The code for the Neural Network, i.e, The AI, or agent, can take four different actions: LEFT, DOWN, RIGHT, or UP. Please follow the instructions in the README.md

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Pickl AI

JULY 23, 2023

In this blog, we will delve into four key types of analytics – Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, and Prescriptive Analytics. Examples of datasets include a spreadsheet containing information about customer demographics, a database of medical records, or a collection of images for training an AI model.

Data Analysis 52

Data Analysis Explainability Algorithm Natural Language Processing 52

Viso.ai

FEBRUARY 12, 2024

True to its name, Explainable AI refers to the tools and methods that explain AI systems and how they arrive at a certain output. Artificial Intelligence (AI) models assist across various domains, from regression-based forecasting models to complex object detection algorithms in deep learning.

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Explainable AI Explainability Deep Learning Neural Network 52

The MLOps Blog

AUGUST 11, 2023

This blog will answer these questions by exploring the following: 1 What is pipeline architecture and design consideration, and what are the advantages of understanding it? These include shared-nothing architecture, event-driven architecture, and directed acyclic graphs (DAGs).

ML 52

ML Machine Learning Data Ingestion Deep Learning 52

deepsense.ai

MARCH 28, 2023

The AI revolution continues, and there is no indication of it nearing the finish line. Diffusion-based models have proven their ability to yield results surpassing all other well-known counterparts used in this domain beforehand, such as Generative Adversarial Networks (GANs) or Variational Autoencoders (VAEs). Sohl-Dickstein et al.’s

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Neural Network Large Language Models Deep Learning Explainability 52

The MLOps Blog

JUNE 27, 2023

Google Cloud Vertex AI Google Cloud Vertex AI provides a unified environment for both automated model development with AutoML and custom model training using popular frameworks. With the help of Neptune, AI teams at Waabi were able to optimize their experiment tracking workflow.

Machine Learning 134

Machine Learning Metadata Data Quality Data Scientist 134

Bugra Akyildiz

FEBRUARY 24, 2024

Responsible AI Development: Phi-2 highlights the importance of considering responsible development practices when building large language models. Trend Spotter on Patrol: Real-time recommendations can identify emerging trends and user interests in real-time, allowing businesses to adapt their offerings and stay ahead of the curve.

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Large Language Models LLM Data Ingestion Neural Network 52

Pickl AI

APRIL 2, 2024

Summary This blog post demystifies data science for business leaders. This blog post serves as a cheat sheet for business leaders, providing a high-level understanding of data science, its applications, and how to leverage it for success. For example, it can identify customers likely to churn or forecast future sales trends.

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