Galaxy’s Head of Mining Amanda Fabiano Departed to Start Consulting Company
Fabiano’s new company will work with Compass Mining and Giga Energy, among others.
Fabiano’s new company will work with Compass Mining and Giga Energy, among others.
Distributed Technologies Research has launched DRAM, a dirham-backed stablecoin that aims to tap into the performance of the United Arab Emirates fiat currency.
An upgrade to the Nomic blockchain will enable the issuance of Bitcoin-based tokens within the Cosmos ecosystem.
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Hong Kong may be providing a haven for crypto investors from war-torn nations and Chinese citizens dodging restrictions.
The Chainalysis cuts follow an earlier 5% workforce reduction in February, reflecting a broader trend of layoffs in the industry.
The bankrupt crypto lender’s restructuring plan includes the establishment of a new entity with $450 million in seed funding.
The one-time “Ethereum killer” remains the darling of institutional investors.
The social media giant tapped the massive cache of posts by Facebook and Instagram users, the “majority” of the content deemed publicly available.
“SBF has simply refused to shut-up,” John Reed Stark opined on Twitter.
A deepfake video shows actor Tom Hanks endorsing a dental plan; Hanks responds it’s not him.
Following Kickstarter’s move, BackerKit is the latest crowdfunding site requiring users to disclose the use of AI-generated images in campaigns.
Today, 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 … Read more
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A 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 … Read more
In 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 … Read more
This is Part 3 of our series where we design and implement an MLOps pipeline for visual quality inspection at the edge. In this post, we focus on how to automate the edge deployment part of the end-to-end MLOps pipeline. We show you how to use AWS IoT Greengrass to manage model inference at the … Read more
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This guest post is co-written by Lydia Lihui Zhang, Business Development Specialist, and Mansi Shah, Software Engineer/Data Scientist, at Planet Labs. The analysis that inspired this post was originally written by Jennifer Reiber Kyle. Amazon SageMaker geospatial capabilities combined with Planet’s satellite data can be used for crop segmentation, and there are numerous applications and … Read more
This 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 … Read more
We’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 … Read more
In the world of data-driven decision-making, time series forecasting is key in enabling businesses to use historical data patterns to anticipate future outcomes. Whether you are working in asset risk management, trading, weather prediction, energy demand forecasting, vital sign monitoring, or traffic analysis, the ability to forecast accurately is crucial for success. In these applications, … Read more
In the rapidly evolving world of AI and machine learning (ML), foundation models (FMs) have shown tremendous potential for driving innovation and unlocking new use cases. However, as organizations increasingly harness the power of FMs, concerns surrounding data privacy, security, added cost, and compliance have become paramount. Regulated and compliance-oriented industries, such as financial services, … Read more
Companies 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 … Read more
From 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 … Read more