EU + Japan: More Than AI Chips!

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Today we will discuss-

• 🚀EU and Japan to collaborate on AI and semiconductors

• 🤖AI market growing at 37% a year: Report

• 😵New York gives job seekers get more transparency with AI

• 🤩11 amazing AI tools you might not have heard of

All this and more - Let's dive in!

👨‍🍳What’s cooking in the newsroom

EU and Japan agree to work together on semiconductor technologies

📰News - EU Commissioner Thierry Breton, on Monday, revealed that The European Union (EU) and Japan have agreed to deepen their cooperation on semiconductors and artificial intelligence.

🧐What were the key factors Breton discussed?

• The EU and Japan will work together to monitor the global chip supply chain. This means they will track how many chips are being made, where they are being made, and who is making them. This information will help them to identify potential risks to the supply chain and take steps to mitigate those risks.

• Further, the EU and Japan will facilitate the exchange of researchers and engineers in the semiconductor field. It simply means they will make it easier for scientists and engineers from both countries to work together on semiconductor research and development.

• The EU will also support Japanese semiconductor companies considering operating within the bloc. This could include providing financial assistance, helping them to find suitable locations, and providing them with access to the EU market.

The deepening cooperation between the EU and Japan comes as the bloc has pledged to reduce its dependence on China.

Demand for AI soars as businesses look to adopt new technologies

📻News - According to a new report by San Francisco-based Grand View Research, the demand for AI-powered products and services has grown by 37% year-over-year. The global AI market is expected to reach $1,811.75 billion by 2028.

This growth is being driven by a number of factors, including the increasing adoption of AI in a wide range of industries, such as healthcare, manufacturing, and retail.

🤔But what in particular is driving AI demand?

• As per the report, big data is making artificial intelligence grow. AI requires a large amount of data to be captured, stored, and analyzed in order to train its algorithms. The ability to analyze big data is giving AI new capabilities that are transforming industries.

• The increasing demand for image processing and identification has also driven the growth of the AI market. Image processing and identification are two of the most important applications of AI, and the demand for these applications is further expected to grow in the coming years.

North America has dominated the AI market and has accounted for a revenue share of over 36.8% of global revenue in 2022.

New York City employers now required to disclose AI's use in hiring

☕News - Starting 5 July, New York City will start enforcing a law that requires employers to disclose if they use artificial intelligence in their hiring process.

The law, which was passed in 2021, also mandates that employers conduct annual third-party audits of their AI tools to ensure that they are not biased against certain types of candidates.

This law is the first of its kind in the United States. It is expected that other cities and states will follow suit in the future.

😎What’s more? The law is designed to protect job seekers from potential misuse of AI in hiring. AI can be used to screen resumes, assess qualifications, and make hiring decisions. However, there are concerns that AI could be used to discriminate against certain groups of candidates, such as people of color or women.

The rules do not require employers to actually use a different screening process if an individual requests one.

Well, the law is still relatively new, so it is not yet clear how it will be interpreted and enforced in practice. However, it is a significant step forward in protecting job seekers from the potential misuse of AI in hiring.

😎What else is happening?

• Elon Musk blames data scraping by AI startups for new Twitter paywalls

• OpenAI shares its insights from global conversations across 22 countries

• George Soros: Artificial Intelligence threatens democracies and helps authoritarians

• Economists fear generative AI's impact on India, Indonesia

• AI-generated fake news sparks rumors of Gary Gensler’s resignation

🎙️AI-based podcast

• The Gradient by Google AI. This podcast features interviews with leading researchers and practitioners in the field of AI. Episodes are released biweekly and are typically around 45 minutes long.

• Data Skeptic by Kyle Polich. The podcast provides a skeptical look at the latest developments in AI. You can listen to fresh perspectives every week.

• Machine Learning Street Talk by Dr. Tim Scarfe. This podcast is hosted by a machine learning researcher and covers a wide range of topics related to machine learning.

 🤯Discover mind-blowing AI tools

1. Phrasee - An AI-powered platform that generates and optimizes marketing messages in real-time

2. DreamyRooms - Allows users to instantly redesign rooms by uploading a picture

3. 30 Stickers - Allows users to create personalized sticker packs using artificial intelligence

4. GenCraft - AI-powered art generator tool that transforms a few words into personalized and stunning art photos

5. Colorify.ai - An AI-powered tool that adds color to black-and-white images

6. Sutro - Utilizes artificial intelligence to revolutionize the process of creating social apps and marketplaces

7. Varaverse - An AI platform that combines Artificial Intelligence and Augmented Reality to create interactive experiences

8. Layerup - An AI-powered tool designed for insurance brokers

9. OwnChat - An AI tool that enables anyone to create their own chat GPT model

10. TechOctave - An all-in-one automated solution for professional blog writing services

11. SongR - Simplifies the process of creating custom songs by generating fully-produced tunes tailored to user preferences

💁🏻Mythbuster

Myth - AI applications are all about the ML code

Fact - AI applications are not just about the ML code. They also require data, infrastructure, and human expertise to be successful. ML code is an essential part of AI applications, but it is not the only component. AI applications also need data to train and learn from, infrastructure to run on, and human expertise to design, develop, and deploy.