Decentralizing the Future: Insights From Wilson Duarte of Hercules

I recently spoke with Wilson Duarte, the Founder of Hercules, a DEX on the Metis network. Wilson has a background in computational applied mathematics and a master’s in numerical simulation in applied Geophysics. During our discussion, we touched on the Metis blockchain, the increasing traction of decentralized exchanges, and the essential security steps these exchanges … Read more

YakDAO Debuts $YAKS Token On Arbitrum, Innovating DeFi Real Estate

**BREVARD, NC, April 2nd, 2024/Chainwire/–**In a significant move within the decentralized finance (DeFi) real estate landscape, YakDAO is set to revolutionize the ecosystem with the launch of its native token, $YAKS, on the Arbitrum network, available for trading on Uniswap starting April 2, 2024. This launch is not just a testament to YakDAO’s innovative approach … Read more

NAVI Protocol Introduces NAVI X Ecosystem Fund To Support Sui Blockchain Development

NEW YORK, United States, April 2nd, 2024/Chainwire/–NAVI Protocol has announced the creation of the NAVI X Ecosystem Fund, committing 10M NAVX tokens to support the growth and innovation of the Sui blockchain’s DeFi and Move-based ecosystem. This initiative aims to provide vital resources for projects at different stages of development, with a focus on enhancing … Read more

Analyzing the Pros, Cons, and Risks of LLMs

Much has been said lately about the wonders of Large Language Models (LLMs). Most of these accolades are deserved. Ask ChatGPT to describe the General Theory of Relativity and you will get a very good (and accurate) answer. However, at the end of the day ChatGPT is still a computer program (as are all other … Read more

C# Collection Expressions and Collection Initializers

I was recently inspired by some interesting performance characteristics for collection initializers and collection expressions in C#, and I wanted to put together an introductory article. This article will be part of a small series where I first introduce you to the syntax we have to work with for both collection expressions and collection initializers … Read more

State of the Noonion 2024: HackerNoon Keeps on Blogging

This is a redacted version of the HackerNoon shareholders’ newsletter by CEO David Smooke and COO Linh Smooke sent to 1.3k shareholders. Picture: HackerNoon Team in an All-Hands Meeting. TL;DR Revenue is slightly down, traffic is slightly up, rate of product development is up, expenses are down, and AI is assisting us but is not replacing us anytime soon 🙂 … Read more

The 30-Day .NET Challenge Day 14: Limit Concurrent Async Operations

Introduction The article highlights the importance of limiting the concurrent asynchronous operations which in turn improves performance. Learning Objectives The common mistake all developers do How to use limit concurrent async operations Best Practices Prerequisites for Developers Basic understanding of C# programming language Basic understanding of asynchronous programming using async await Getting Started The common … Read more

Crypto Market Recap: XRP Feels the Heat

Crypto Market Recap: 04/02 Buckle up because the crypto market this week was a wild ride, even for seasoned investors. Bitcoin (BTC), fresh off its best monthly close ever, took a surprising 4% tumble, failing to recapture the glory of that milestone. This price swing highlights the ever-present tension in the crypto sphere: fear of … Read more

Outdoor Tech That Works: Stay Warm and Dry in the Harshest Conditions

Following its breakout year in 2023, generative AI (genAI) is finding increasing applications across various industries, including fashion. However, while this is a significant technology, it’s only one aspect of the changes happening in the field. Some innovations may not appear on the catwalks or make headlines but could be essential during mountain expeditions or … Read more

PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Experimental Results

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more

PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Opportunities

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more

PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Motivation

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more

PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Experiments

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more

PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Conclusion & References

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more

PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Arithmetic Intensity

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more

PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Hardware Details

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more

Modeling Workload Interference

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more

Proble Formulation: Two-Phase Tuning

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more

PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Abstract & Introduction

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more

PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Predictor Analysis

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more

PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Architecture Overview

:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Minghao Yan, University of Wisconsin-Madison; (2) Hongyi Wang, Carnegie Mellon University; (3) Shivaram Venkataraman, myan@cs.wisc.edu. ::: Table of Links Abstract & Introduction Motivation Opportunities Architecture Overview Proble Formulation: Two-Phase Tuning Modeling Workload Interference Experiments Conclusion & References A. Hardware Details … Read more

What Is the Technology Supercycle?

At SXSW this year, Amy Webb, CEO of the Future Today Institute, once again delivered a session as a lighthouse in the “technology supercycle” reshaping our world. Webb, a renowned author and professor at NYU Stern School of Business, shared key insights from the 17th Annual Technology Trends Report in an enlightening one-hour session. Despite … Read more

What Daylight Are We Saving? Time Data Series

Welcome to Daylight Savings Recovery Week – a period of days when most of the world expresses shock, dismay, despair, and the other 5 stages of grief about waking up an hour early and generally being cranky. Like so many things in 2024, the act of saving daylight (whatever that might actually mean) has become … Read more

Step Towards Sci-Fi: AI and BCI Insights From SXSW

Imagine we’re stepping into a sci-fi movie, but it’s real life. That’s the vibe at SXSW sessions, where tomorrow’s ideas feel like they’re unfolding today. In one of the first talks I caught at SXSW this year, Elizabeth Bramson-Boudreau, the big boss at MIT Technology Review, laid out a list of ten tech breakthroughs. She’s … Read more

Mastering Product Engagement: Amplifying Interaction Through Strategic Marketing (Part I)

Maintaining user attention has become more challenging than ever, however, companies can take different steps to engage their audience. Drawing from my experience in marketing, I have seen what works and what doesn’t, which ultimately determines the success of a product. Businesses can amplify the interaction between users and their tech products by leveraging strategic … Read more