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🪐 What’s happening in tech today, May 4, 2024?

The HackerNoon Newsletter brings the HackerNoon homepage straight to your inbox. On this day, Margaret Thatcher becomes Prime Minister happened in 1979, and we present you with these top quality stories. From EigenLayer Airdrop Has Highlighted the Problems in the Crypto Market to Working With Wav2vec2 Part 1: Finetuning XLS-R for Automatic Speech Recognition, let’s dive right in.

The Market Today

#02

Facebook (Meta)

$451.96 + 1.33%

#04

Microsoft

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#05

ThoughtWorks

$2.25 -6.67%

#06

Roblox

$39.24 + 1.30%

#14

Amazon

$186.21 -0.42%

#01

Bitcoin

$63727.85 + 3.24%

EigenLayer Airdrop Has Highlighted the Problems in the Crypto Market

TL;DR Eigen Layer airdrop illustrates a mismatch in users expectations and market conditions. Why is the community angry with the biggest Ethereum restaking platform Read More.

By @dariavolkova [ 6 Min read ]

Hi everyone, Daria Strategy here 🙌🏻

I’m a Growth Marketer, Brand Strategist and Communications expert working with blockchain and crypto projects. I create additional value and build brand awareness of the Web3 companies among users, developers, and VC funds.

Recently, the crypto market exploded with news about the airdrop of EigenLayer, the most hyped Ethereum restaking platform. The conditions for receiving this drop caused an even greater explosion of emotions, discussions, and even hate.

The project offers a platform for those who want to restake rather than the classic staking process that attracts regulators' attention. The emergence of EigenLayer and LRT restaking protocols increased ETH's share of staking to 26% of the total supply. According to DeFi Lama, EigenLayer is TVL's second-largest protocol on Ethereum after Lido, at $14.2 billion:..

Working With Wav2vec2 Part 1: Finetuning XLS-R for Automatic Speech Recognition

TL;DR Step-by-step guide on how to finetune wav2vec2 XLS-R for automatic speech recognition using a Spanish language training dataset. Read More.

By @pictureinthenoise [ 29 Min read ]

Meta AI introduced wav2vec2 XLS-R ("XLS-R") at the end of 2021. XLS-R is a machine learning ("ML") model for cross-lingual speech representations learning; and it was trained on over 400,000 hours of publicly available speech audio across 128 languages. Upon its release, the model represented a leap over Meta AI's XLSR-53 cross-lingual model which was trained on approximately 50,000 hours of speech audio across 53 languages.

This guide explains the steps to finetune XLS-R for automatic speech recognition ("ASR") using a Kaggle Notebook. The model will be finetuned on Chilean Spanish, but the general steps can be followed to finetune XLS-R on different languages that you desire.

Running inference on the finetuned model will be described in a companion tutorial making this guide the first of two parts. I decided to create a separate inference-specific guide as this finetuning guide became a bit long...

Read Code Like a Hacker With the SAST

TL;DR Static application security testing (SAST) is a subset of static code analysis used to increase the security and reliability of the code. Read More.

By @matejsmycka [ 4 Min read ]

Reading code manually is a time-consuming process. It is also error-prone, as it is easy to miss important details. As developers and penetration testers, we need to find a way to automate this process. SAST is a technique that can help us with this task.

SAST is not a silver bullet. It is usable only for use cases with access to the source code for open-source projects or white-box penetration testing. However, it can help you find some low-hanging fruits and save time.

Static application security testing (SAST) is a subset of static code analysis used to increase the security and reliability of the code. SAST detects old dependencies, secret detection, logical errors that lead to vulnerabilities, and more. SAST includes testing that affects cybersecurity secondarily, such as visual code complexity, code ambiguity, and non-intuitive practices that can lead to vulnerabilities...

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On This Day

Margaret Thatcher becomes Prime Minister

Margaret Thatcher became the Prime Minister of the United Kingdom on May 4, 1979, following the victory of the Conservative Party in the general election. She was the first woman to hold the position of Prime Minister in the UK, and she remained in office for three consecutive terms until November 28, 1990. During her time in office, Thatcher implemented a series of policies aimed at reforming the British economy and reducing the power of trade unions. Her approach, which became known as Thatcherism, emphasized free-market capitalism, privatization, and deregulation. She also played a significant role in foreign affairs, particularly during the Cold War, where she was a strong ally of the United States and a vocal opponent of the Soviet Union. Thatcher's leadership style was often controversial, and her policies were divisive, leading to protests and social unrest. However, she is widely recognized as a transformative figure in British politics, who left a lasting impact on the country and its economy.