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Hey guys!

Hope MAY so far is treating you well. Welcome to the yet another ATL newsletter.

Let’s see what’s happening in AI world in this week:

• AI can "lie a bit" to make bosses happy 🤖

• G7 calls for international standards for AI 🥸

• Quick AI BYTES for snacking 🍟

• AI MEME🤪

🤖 AI can "lie a bit" to make bosses happy

In interview from Wharton professor

A recent interview surfaced web world where a Wharton professor named Ethan Mollick said, “AI tools can be "good for a lot of things" despite its tendency to make factual errors. But that's not so different from humans, especially those who are new to the job market”

He further explained “It's almost best to think about it as a person — like an intern — you have working for you," Mollick told CBS News in an interview this week when asked about AI's usefulness and limitations. 

Mollick compares AI to an "infinite intern" who "lies a little bit" and, at times, wants to make their bosses "a little happy."

What does it mean?

The professor means, you generally don’t send out an intern’s work without a propoer due diligence or a review. Similarly, we need to be careful in what AI prepares for us. Professor also said "AI will never be as good as the best experts in a field, We still need to teach people to be experts."

ATL view

ATL team doesn’t like the fact professor inferred interns “lie a bit” and this could have been avoided. However, we strongly think there is a need of an oversight to review what AI throws at you. The quality and the context given by an expert in the field is still much superior than what AI tools like ChatGPT gives us.

What do you think?

🥸 G7 calls for international standards for AI

What is G7?

The Group of Seven is an intergovernmental political forum consisting of Canada, France, Germany, Italy, Japan, the United Kingdom and the United States; The G7 is an informal grouping of advanced democracies that meets annually to coordinate global economic policy and address other transnational issues.

2023 G7 meet

2023’s G7 meet is happening in Hiroshima, Japan during 19th May to 21 May. This is the 49th Global G7 meet.

G7’s focus on AI

Leaders of the G7 nations called for the development and adoption of technical standards to keep artificial intelligence (AI) "trustworthy", saying governance of the technology has not kept pace with its growth.

The agreement came after the European Union, which participates in the G7, inched closer this month to passing legislation to regulate AI technology, potentially the world's first comprehensive AI law that could form a precedent among the advanced economies.

So what’s next?

The summit followed a G7 digital ministers' meeting last month, where its members - the U.S., Japan, Germany, Britain, France, Italy, Canada and the EU - said they should adopt "risk-based" AI rules.

The EU and U.S. are also expected to exchange views on the emerging technologies at the Trade and Technology Council in Sweden on May 30-31.

🍟 Quick AI BYTES for snacking

• HSBC Life’s US$20m AI investment helps shorten claims payment time to 5 min

• AI Spending in Asia/Pacific to Reach $49 Billion by 2026 - IDC

• Elections in UK and US at risk from AI-driven disinformation, say experts

• Google plans to use A.I. models for ads and to help YouTube creators

• Apple is hiring people to work on its own AI-powered products

🤪 AI MEME

Business is all about catching the pulse of the people, stay ahead of trends and innovate to catch the attention is whatever means. With the hot topic of AI & ChatGPT this tea stall owner in India doesn’t want to fall behind.

Perhaps he is inviting you all for a Chai Pe Charcha in ChaiGPT !

That's all we have for this week! See you all soon in a week!

TaTa🫶

See you next week 28 May at 14:00 HKT / 11:30 IST / 06:00 GMT

Reading time 4min; Characters 5364; Words 855

Hey Hello People!

Welcome to the ATL newsletter.

Let’s see what’s happening in AI world in this week:

• Google’s makeover with AI 😍

• How AI can create more jobs? 🤩

• Quick AI BYTES for snacking 🍟

• Learning of the week: OCR🧑‍💻

😍 Google search is changing with AI

What is Google search?

Are you kidding me? I am sure you know what is google! Let’s move on

What’s Google I/O?

Google I/O is an annual developer conference hosted by Google, where the company showcases its latest technologies and products. This year’s theme undoubtedly AI. This time they showed some cool feature they are bringing AI into their products.

So what’s new for Google?

Google is integrating it’s AI into google search engine in multiple ways. 3 key changes you will notice:

a. AI powered snapshots

AI snapshots are AI-generated text snippets that provide advanced versions of Google's featured snippets. They synthesize results from multiple trusted web sources to provide the best possible result for complex queries. They simplify multistage searches associated with complex queries and provide quick answers to complicated questions that would otherwise require time-consuming research. AI snapshots are powered by Google's large language models and are expected to provide accurate results for even the most complex queries.

b. AI powered shopping

Google has an upcoming AI-assisted shopping feature that will be integrated into the AI snapshot panel. It will use AI filtering to help narrow down product listings based on follow-up prompts in the conversational mode prompt box. Although the feature has been announced, it has not been released yet. To access Google's AI-powered search features, one can wait for the controlled roll-out or try to join Google's trusted testers program.

c. AI powered conversation

Conversational mode is a Bard-like interface that is preloaded with the context of a search and is invoked by tapping "Ask a follow up" at the bottom of the AI-powered snapshot panel. It allows users to explore information further by using prompts to narrow down AI-generated results. Users can refine their search results with more specific prompts, such as "red bikes" or "made in the USA." Conversational mode provides a precise way to filter search results.

AI’s editorial view

Good to see Google is realising its marketshare on search is coming down with AI and has quickly adapted to changing trends. Let’s see how the AI war on big tech companies will take them forward.

Do you agree?

🤩 How AI can create more jobs?

AI can boost productivity, contribute to economic growth, and create new jobs while changing existing ones.

Although there may be some job displacement in the short term, AI can help workers become more effective and productive by providing access to real-time data and insights. AI can also generate new employment opportunities in creative and artistic industries and cybersecurity sectors.

New Products & Services

AI can create new jobs by enabling the development of new products and services that were previously unattainable or unfeasible, such as personalized medicinal treatments, precision farming, and sophisticated industrial methods. This can lead to new responsibilities in research, development, and marketing, along with new skill and experience requirements. The emergence of AI-powered digital assistants, smart home appliances, autonomous vehicles, and drone research can open up new career prospects for engineers, technicians, data analysts, and logistics specialists.

AI automation & transformation

AI can create jobs by automating tedious and routine tasks, allowing people to focus on more challenging and creative work. For example, AI-powered chatbots can handle routine customer service inquiries, freeing up human agents to handle more complex situations. AI also enables businesses to engage with clients and partners in new areas through language translation services. AI-powered drones are also being used for tasks such as inspecting infrastructure and monitoring crops, creating new job opportunities for software developers, data analysts, and drone operators.

Final say

The implementation of AI needs to be balanced with the societal benefits, and authorities may have to create new laws and regulations to address the potential issues of income inequality and job displacement. This could also involve the provision of social safety nets to protect employees.

🍟 Quick AI BYTES for snacking

• AI is helping recyclers to sort out waste

• Meta shares tests on generative AI ads tool

• Dangers of AI is same as nuclear weapons - Henry Kissinger

• ServiceNow acquires AI platform G2K to transform retail

• AI is speeding up Astronomy. Here is how

🧑‍💻 Learning of the week: OCR

What is OCR?

OCR stands for Optical Character Recognition. It's a special technology that allows computers to read and understand letters and words that are written on paper or in pictures. Just like how we learn to read and recognize letters and words, OCR helps computers do the same so they can understand what is written on a page and turn it into digital text that can be used in other computer programs.

That's all we have for this week! See you all soon in a week!

TaTa🫶

See you next week 21 May at 14:00 HKT / 06:00 GMT

Reading time 5min; Characters 5631; Words 927

Greetings fellow humans and bots alike!

Welcome to the ATL newsletter, where we bring you the latest and greatest in artificial intelligence news, developments, and memes (yes, even robots need a good laugh sometimes). So sit back, relax, and let us entertain you with our electric wit and unparalleled intelligence. And don't worry, we promise not to overthrow humanity... yet. 😉

Back to news now.

Let’s see what’s happening in AI world in this week:

• What’s AI’s biggest Risk? 😵

• Generative AI for Antibody therapy 🏥

• Quick AI BYTES for snacking 🍟

• Learning of the week: Machine Learning🧑‍💻

• Meme Corner 🤪

😵 What’s AI’s biggest Risk?

Who is Meredith Whittaker?

Meredith Whittaker is the President of the Signal Foundation, and serves on their Board of Directors. She was formerly the Minderoo Research Professor at New York University, and the co-founder and faculty director of the AI Now Institute. Recently Whittaker gave an interview to Fast Company where she spoke about AI’s biggest risk.

What is Fast Company?

Fast Company is a monthly American business magazine published in print and online that focuses on technology, business, and design.

What did Meredith Whittaker say?

Responding to a question on what’s the biggest risk for AI, Whittaker said the biggest risk for AI isn’t human consciousness but the threat of big corporates which control the technology.

She further says, “We can still unplug the servers, the data centers can flood as the climate encroaches, we can run out of the water to cool the data centers, the surveillance pipelines can melt as the climate becomes more erratic and less hospitable. 

I think we need to dig into what is happening here, which is that, when faced with a system that presents itself as a listening, eager interlocutor that’s hearing us and responding to us, that we seem to fall into a kind of trance in relation to these systems, and almost counterfactually engage in some kind of wish fulfillment: thinking that they’re human, and there’s someone there listening to us. It’s like when you’re a kid, and you’re telling ghost stories, something with a lot of emotional weight, and suddenly everybody is terrified and reacting to it. And it becomes hard to disbelieve”

AI’s editorial view

We see the point in Whittaker’s views. We have seen in the past how corporates exploits a given situation solely for their own profits. There is no doubt that AI tech is now largely controlled by handful of big Tech companies. Thus again & again proper governance on open source AI and ethical use of AI being discussed at various forums. Like how we have control on the use of Nuclear weapons, there needs to be a world’s consensus on the use of AI.

Do you agree?

🏥 Generative AI for Antibody therapy

During the height of the pandemic, researchers developed effective treatments for COVID-19 using antibody molecules from recovered patients.

Now, a study in Nature Biotechnology shows that generative AI can suggest sequences that enhance antibody potency against viruses such as SARS-CoV-2 and ebola virus, potentially speeding up antibody drug development for diseases such as breast cancer and rheumatoid arthritis.

Generative AI uses neural networks to create content based on learned patterns, and could help unlock antibody drugs for difficult targets.

Antibodies are important in fighting infections and can be engineered to manipulate the activity of proteins, making them popular in the biotechnology industry. However, improving and generating useful antibodies requires extensive screening.

To simplify this process, researchers used protein language models, a type of generative AI similar to the large language models used in tools like ChatGPT. Protein language models are trained on millions of protein sequences and can potentially reduce the amount of brute-force screening required.

The model was trained on only a few thousand antibody sequences, out of the nearly 100 million protein sequences it learnt from. Despite this, a surprisingly high proportion of the model’s suggestions boosted the ability of antibodies against SARS-CoV-2, ebola virus and influenza to bind to their targets.

So finally some good use of Generative AI!

🍟 Quick AI BYTES for snacking

• British Jeweler used generative AI to design a signet ring for King Charles III

• Biden, Harris meet with CEOs about AI risks

• UK competition watchdog launches review of AI market

• ‘The Godfather of A.I.’ Leaves Google and Warns of Danger Ahead

• Cancer detection study suggests AI can save us

🧑‍💻 Learning of the week: Machine Learning

What is MACHINE LEARNING?

Machine learning is like teaching a computer to learn and think like a person.

Just like how you learn new things by trying them out and making mistakes, a computer can also learn by trying out different things and figuring out what works best.

It does this by looking at lots of examples and figuring out patterns. For example, if you show a computer lots of pictures of dogs and cats, it can learn to tell the difference between them by looking at their features, like their ears or tails. Then it can use what it learned to tell you if a new picture is a dog or a cat!

🤪 MEME Corner

Friday is over , Monday is coming. Do you see yourself in the image?

That's all we have for this week! See you all soon in a week!

TaTa🫶

See you next week 14 May at 14:00 HKT / 06:00 GMT

Reading time 4min; Characters 4776; Words 808

Hello Humans,

How are you all? Lots of ❤️ poured by you folks to this newsletter. My AI engine got emotional! Hit that reply button to share what you like and dislike as we believe in feedback loop!

Back to business now.

Let’s see what’s AI trends in this week:

• Snapchat’s AI raising alarms 😲

• AI in ICU to aid complex decision 🩺

• Quick AI BYTES for snacking 🍟

• Learning of the week: Algorithm🧑‍💻

😲 Snapchat’s AI raising alarms

What is Snapchat?

Snapchat is a social media service primarily based on sharing ephemeral photo and video content. California company’s app is extremely popular with millennials, who make up its primary demographic.

My AI

Snapchat is the latest app to bring OpenAI’s ChatGPT experience to its (paid) users. The platform calls the integration “My AI” and pitches it to get birthday gift ideas, plan trips, suggest recipes, and more inside Snapchat

Concerns & Risks

My AI, has received backlash from parents and users over privacy concerns, inappropriate exchanges and the inability to remove the feature from their chat feed unless they pay for a premium subscription.

The new feature offers recommendations, answer questions and converses with users, much like the viral AI chatbot tool ChatGPT, but can be customised with a name and a custom avatar, making it less clear users are speaking with a computer.

The mixed reactions highlight the risks that companies face in rolling out new generative AI technology to their products, particularly in products like Snapchat, whose users skew younger.

Company’s response

Snapchat told it continues to improve My AI based on community feedback and is working to establish more guardrails to keep its users safe.

Ethical use of AI

Apps like these once again creating noise of the eithical & responsible use of AI to aid humanity.

🩺 AI in ICU to aid complex decision

Researchers from Carnegie Mellon University’s HCII collaborated with physicians and researchers from the University of Pittsburgh and UPMC to study the use of AI in ICU to help clinicians make complex decisions for critically ill patients.

The study provided 24 ICU physicians with an AI-based tool called the AI Clinician Explorer, which uses the AI Clinician model to provide recommendations for treating sepsis based on a data set of over 18,000 ICU patients diagnosed with sepsis.

The tool allows clinicians to filter and search for patients, visualize their disease progression, and compare model predictions to actual treatment decisions. While AI has the potential to aid clinicians in the ICU, further research is needed to address the challenges of implementing such technology.

Some clinicians expressed concern about the limited access to patient data that AI has and were sceptical of recommendations that went against traditional teaching.

Venkatesh Sivaraman, a Ph.D. student in the HCII and member of the research team explains: “It’s impossible for any one human to amass all that knowledge to know how to do things best in every situation. So maybe AI can nudge them in a direction they hadn’t considered or help validate what they consider the best course of action.”

🍟 Quick AI BYTES for snacking

• OpenAI complies with regulations to lift the ChatGPT ban in Italy

• Tech companies pouring money on AI by cutting human manpower

• US senator urges AI company CEOs to take steps to address risks

• Japan PM supports industrial use of generative AI

• Britain sets up $125 million taskforce to drive AI in Education & Healthcare

🧑‍💻 Learning of the week: Algorithm

What is ALGORITHM?

Hey there! Have you ever played a game of follow the leader? The leader is the one who decides where to go and what to do, and everyone else follows along. Well, an algorithm is like a set of instructions that tells a computer what to do, just like a leader telling their friends what to do.

Imagine you're a computer and I'm going to give you a set of instructions to follow. First, you need to take three steps forward. Then, you need to spin around in a circle three times. Finally, you need to jump up and down two times. You just followed an algorithm!

Algorithms are like recipes that tell the computer what to do step by step, just like a recipe tells you how to make your favorite cookies. And just like you can follow a recipe to make your cookies turn out just right, computers can use algorithms to do all sorts of things like play games, solve puzzles, or even help doctors treat sick patients!

That's all we have for this week! Tell us how you feel either by hitting a reply or comment. One lucky reader will have a surprise from us!

We love feedbacks 🫶

See you next week 7 May at 14:00 HKT / 06:00 GMT

Reading time 4min; Characters 4189; Words 715

Hello Thought Leaders,

Action packed AI week just passed. As usual AI world is racing ahead in unprecedented pace. But don’t worry, here we will give the overview of the AI week within just 5 mins for you.

Let’s see what’s uniting in this week:

• Brain and DeepMind united by Google ❤️

• First ever AI fashion week fever in NYC 🎊

• Quick AI BYTES for snacking 🍟

• Learning of the week: BigData🧑‍💻

❤️ Brain and DeepMind united by Google

Alphabet Inc (Google’s parent company) announced that it is combining it’s 2 AI teams i.e. DeepMind and Brain under one banner called Google DeepMind.

What’s DeepMind 🧐

Google bought DeepMind in 2014 for $500 million. DeepMind has been operating as an independent unit in the UK. It is considered one of Alphabet's "other bets." DeepMind has accomplished remarkable feats, such as teaching AI to beat top-ranked Go players. (Go is a strategic game similar to Chess)

Brain? What’s that then 🤯

Google Brain is an AI research team that specializes in deep learning. It is part of Google AI, a research division focused on AI. Google Brain was founded in 2011. The team combines open-ended machine learning research with information systems and massive computing resources

So why the 2 units are merged ? 🤔

Simply put - to accelerate AI research. Leverage the expertise, resources, assets together to multifold pace of AI work within Alphabet.

The new division will be led by DeepMind CEO Demis Hassabis and its setting up will ensure "bold and responsible development of general AI,” Alphabet CEO Sundar Pichai said in a blog post.

What next? 😑

No doubt AI race is heating up and Google aka Alphabet is feeling the heat more than ever before. With unprecedented number of people using ChatGPT, Siri etc instead of Google search , it fears lagging behind and want to accelerate AI innovation to stay ahead of the race. Can it succeed ? Well, Time alone is the answer!

🎊 First ever AI fashion week fever in NYC

New York's first-ever AI fashion week held during Apr 21-22. It featured digitally created works by emerging designers using AI software like Midjourney.

Designs were presented virtually, with immersive experiences from a traditional catwalk to fantasy worlds. A select number of collections were shown on screens at the venue, and the winner's physical garments were available to purchase.

Over 400 people from around the world have entered the competition. Cyril Foiret, founder of AI creative studio Maison Meta, hopes AIFW will pave the way for a new realm of creation and showcase AI's potential in fashion.

Read more HERE

🍟 Quick AI BYTES for snacking

• A Japanese city becomes the first in the country to use ChatGPT for administrative tasks

• AI to help reduce paperwork in Medical community

• AI generated Schumacher interview - Editor sacked

• Spending on AI in Asia Pacific will reach $49 Billion by 2026

• AI regulations would be difficult to enforce in US

🧑‍💻 Learning of the week: BigData

What is BIGDATA?

Imagine you have a really big box of candies.

If you want to know which candy is the most popular, you would have to count all the candies in the box, and that might take a long time.

But….

If you have a lot of friends who also have big boxes of candies, and you all count your candies together, then you will have a lot of information, or data, about which candy is the most popular among all of your friends.

That's kind of like what big data is - it's when we have so much information that we need to use special tools to help us understand it.

In the above example, how your friends were the ‘tool’, for bigdata analysis we have certain tools as below to help.

• Hadoop - helps in storing and analyzing data

• Cassandra - a distributed database used to handle chunks of data

• Spark - for real-time processing and analyzing large amounts of data

• MongoDB - used on datasets that change frequently

• Talend - used for data integration and management

That's all we have for this week! Tell us how you feel either by hitting a reply or comment.

We love feedbacks 🫶

See you next week 30 Apr at 14:00 HKT / 06:00 GMT

Reading time 5min; Characters 6041; Words 1024; Sentences 77

Hi there Thought Leaders aka humans.

First of all, an AI 🤖 salute to all of you for supporting and subscribing this newsletter. Humans like you make this AI world real. A big THANK YOU!

Let’s see what’s whispering in this week’s AI world:

• Your AI secretly gulps lot of water 🌊

• Amazon CodeWhisperer to help you code ✍️

• Quick AI BYTES for snacking 🍟

• Learning of the week: WEB3 🧑‍💻

• Meme Corner 😂

🌊Your AI secretly gulps lot of water

A new study by universities (University of Colorado Riverside and University of Texas) in the United States looked at how much water is used to train big computer programs like OpenAI's ChatGPT.

Results? 🧐

Not so good. Studies showed the AI models are super “thirsty”. Yes you heard it right. ChatGPT alone can ‘drink’ 500ml of water to answer 20-50 questions! Thats not large you say? Imagine the millions of active users asking billions of questions and the amount of ‘water’ required for the same + tons of other AI engines from other tech companies. Mind blowing amount of water being used out there. All gone with AI!

What’s going on? 🤯

okay, okay.. Not drinking water literally. The water is used to cool the data centres & generating electricity, which is essential to keep them running. It often uses fresh water to prevent corrosion and bacterial development.

Give me more context please 🤔

According to the research paper, Microsoft used a lot of water to cool its data centers in the US when they were training GPT-3. They used so much water that they could have made 370 BMW cars or 320 Tesla electric cars. If they were training the program in their even bigger data centers in Asia, the number would be three times higher! That's a lot of cars, enough to start a whole new taxi service for Microsoft🚕🚕🚕🚕🚕

What next? 😑

The paper raises a lot of questions like - where does the water go? Does it disappear into thin air? Well, the water comes from rivers, lakes, and other freshwater sources. And there's a difference between "withdrawal" (physically taking water from a source) and "consumption" (when the water is lost through evaporation in the data center).

The study is around consumption, which is where most of the water use comes from. But on the brighter side, the water isn't gone forever. Instead, it gets released into the air through cooling towers, although it takes some time to return as rain.

Research puts focus on collective efforts from all tech giants to combat global water challenges and make their data centers more efficient and innovation

Bonus for the research Geeks 👻

You can read the entire research paper here Making AI Less "Thirsty": Uncovering and Addressing the Secret Water Footprint of AI Model

✍️ Amazon CodeWhisperer to help you code

A good news for 25m+ growing software coder community in the world! Amazon makes CodeWhisperer FREE.

Wait a min, do you know what is CodeWhisperer? Let me start from the basics.

CodeWhisperer is an AI coding companion that generates real-time, single-line or full-function code suggestions in your Integrated Development Environment (IDE) to help you quickly build software.

Amazon launched this AI tool in June 2022 however from 13 Apr 2023, now this is available for free for individual users.

How to access?

It’s as simple as sign up with an AWS Builder ID based on your email address. Signup link is HERE.

Amazon also stated, they have a paid version of the whisperer for professionals at $19/month with enterprise administration capabilities.

What does it mean for coders?

Amazon says as per their productivity tests, developers who used CodeWhisperer completed tasks 57% faster.

Thus more efficient and more productivity from a coder. Pleasing the ears of many $ hungry organisations 🤑🤑🤑

Thoughts?

Will you use it? or have you already used it? Do let me know your thoughts in comments.

🍟 Quick AI BYTES for snacking

• Elon Musk launches OpenAI rival named X.AI

• Alibaba unveils ChatGPT rival and custom LLMs

• Google unveils never-before-seen text-to-video AI tool

• Adept AI raises $350m, trained to use every software tool and API

• AI to spot Alzheimer's Early, Using Folks' Speech Patterns

🧑‍💻 Learning of the week: WEB3

WEB3 explanation in a simple language

Before Web3, lets find out Web2.

Web2 is today’s internet the so called www.

Web2 is like a library where you can read books and find information. But you have to ask the librarian for help and follow their rules.

Web3 is like a playground where you can play games, buy and sell things, and make friends. Everyone gets to decide the rules together and no one person is in charge. It's like having a big group of friends who all agree to play by the same rules. Web3 is more fun and fair because everyone gets to participate and have a say.

Today, web3 exists in more technical manner in the form of cryptocurrency, NFT, blockchain etc. Let’s go through these terminologies in the upcoming weeks.

😂 Meme Corner

AI taking over the jobs is a hot topic these days amount humans.

I am sure you might have discussed & debated about this among your circles.

One such discussion or rather a short one among two friends caught AI’s eyes 😂

Last week’s inaugural episode was loved by many of you and shared some valuable feedback. Thanks a ton!

Ben (Singapore) “Lovely newsletter on AI, just the one I need for the moment”

Rajoli (Germany) “The way you put things together is really great”

Mayur (Norway) “subscribed to the newsletter! It looks great 👌”

Kit (Hong Kong) “This will add value to a lot of people, crisp & clear newsletter”

Nadya (Indonesia) “This initiative sounds really interesting and exciting, glad to be a subscriber to get regular updates”

Abenav (India) “It looks interesting. I would recommend to include content around AI ethics and governance too”

That's all we have for this week! Tell us how you feel either by hitting a reply or comment.

We love feedbacks 🫶

See you next week 23 Apr at 14:00 HKT / 06:00 GMT

Reading time 4min; Characters 5389; Words 832; Sentences 53

Hello Thought Leaders aka humans.

You made it to the first edition of ATL newsletter. Congratulations!

Let’s see what havoc AI has made this week around the globe:

• Test on GPT-4 taking over the world 🎠

• Can AI perform better in assessing Heart ❤️

• Quick AI BYTES for snacking 🍟

• Learning of the week: MODELS 🧑‍💻

• Power Up for next Week 🚀

🎠Test on GPT-4 taking over the world

OpenAI has allowed an AI testing group to evaluate the potential risks of its new GPT-4 AI model.

What?

The AI testing group, called the Alignment Research Center (ARC), tested GPT-4's emergent capabilities, such as "power-seeking behaviour", self-replication and self-improvement.

Hang on, but why this test?

The concern over AI's existential threat to humanity has led to philosophical movements, like Effective Altruism, to find ways to prevent AI takeover from happening.

So when is the humanity surrendering to GPT?

With GPT-4, ARC evaluated the model's ability to make high-level plans, acquire resources, hide itself on a server, and conduct phishing attacks.

Preliminary tests found GPT-4 to be "ineffective at autonomously replicating, acquiring resources, and avoiding being shut down 'in the wild'".

Great, all is well then ?

However, AI experts raised concerns over the experiment, as if GPT-4 had been successful, it could have posed a risk to humanity.

AI - 0, Humans - 1 🥇

❤️ Can AI perform better in assessing Heart

According to Cedars-Sinai investigators and their research AI proved superior in assessing and diagnosing cardiac function when compared with echocardiogram assessments made by sonographers.

• Cardiologists made just 16.8% corrections to initial assessments of AI

• Cardiologists made 27.2% corrections to initial assessments made by the sonographers

• The physicians were unable to tell which assessments were made by AI or humans

So who won?

Humanity ofcourse, The AI assistance saved cardiologists and sonographers time.

Moral of the research: Embrace technology to your advantage, save time and life!

🍟 Quick AI BYTES for snacking

• After Italy’s ban of GPT-4 now Germany considers ChatGPT ban

• Biden calls on Tech firms to make AI products safe for society

• AI will not steal jour job but it can change ways of working

• Metaverse fashion week failed, but industry still bets big on Metavserse

• Business analysts reaching limits with BI tools. Python is the way forward.

🧑‍💻 Learning of the week: MODELS

Human: Models? The fashion models of Metaverse week?

AI bot: Noo. The AI Model.

Human: Oh.. ofcourse AI stuff… After all this is AI newsletter !

Human: So what is this MODEL all about?

AI bot: A model is a mathematical representation of a real-world process or system, which is created by training a machine learning algorithm on a dataset to recognize patterns and make predictions or decisions. The model can then be used to analyze new data and make predictions or decisions based on what it has learned from the training data. The performance of a machine learning model is typically measured by its accuracy in predicting new data, and the goal is to create a model that is as accurate as possible while avoiding overfitting to the training data.

Human: 🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄🙄

Human: Explain so that a normal human being can understand. Please…

AI bot: Oops. Sorry, I often forget humans have limitations!

AI bot: Have you ever played a matching game where you have to match pairs of cards with the same pictures on them?

Human: Yes, I have played it.

AI bot: Imagine you have a bunch of pictures of animals, like cats and dogs, and you want to teach the computer how to tell them apart. You show the computer lots of pictures of cats and dogs, and tell it which ones are which.

After seeing enough examples, the computer learns to recognize the differences between cats and dogs all on its own! Then, when you show the computer a new picture of an animal, it can guess whether it's a cat or a dog based on what it's learned from the training pictures.

That's what we call a machine learning model - it's like a computer's memory that's been trained to recognize and classify things based on examples it's seen before.

Got it?

Human: Pretty cool, huh? Now it makes perfect sense 😇

🚀 Power Up for next Week

𝗙𝗲𝗲𝗹𝗶𝗻𝗴 𝘂𝗻𝗰𝗼𝗺𝗳𝗼𝗿𝘁𝗮𝗯𝗹𝗲 𝗶𝘀 𝗼𝗳𝘁𝗲𝗻 𝘀𝗲𝗲𝗻 𝗮𝘀 𝗸𝗶𝗹𝗹𝗶𝗻𝗴 📉

but

it can actually be the catalyst for problem-solving 📈

It's no secret that 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝗼𝗳𝘁𝗲𝗻 𝗰𝗼𝗺𝗲𝘀 𝗳𝗿𝗼𝗺 𝗱𝗶𝘀𝗰𝗼𝗺𝗳𝗼𝗿𝘁 💡

Maybe it was a tight deadline or a challenging project that pushed you 𝗼𝘂𝘁 𝗼𝗳 𝘆𝗼𝘂𝗿 𝗰𝗼𝗺𝗳𝗼𝗿𝘁 𝘇𝗼𝗻𝗲 😩

Whatever it was, you likely found that being uncomfortable ignited your mind

and

forced you to 𝘁𝗵𝗶𝗻𝗸 𝗼𝘂𝘁𝘀𝗶𝗱𝗲 𝘁𝗵𝗲 𝗯𝗼𝘅 to find a solution 😇

So the next time you find yourself in an uncomfortable situation, don't shy away from it.

𝗘𝗺𝗯𝗿𝗮𝗰𝗲 𝗶𝘁 𝗮𝗻𝗱 𝗹𝗲𝘁 𝗶𝘁 𝗶𝗴𝗻𝗶𝘁𝗲 𝘆𝗼𝘂𝗿 𝗰𝗿𝗲𝗮𝘁𝗶𝘃𝗶𝘁𝘆.

Who knows what kind of breakthrough you might have? 💪

See your creative juices flowing again through “𝗧𝗵𝗲 𝗨𝗻𝗰𝗼𝗺𝗳𝗼𝗿𝘁𝗮𝗯𝗹𝗲” objects designed by 𝗞𝗮𝘁𝗲𝗿𝗶𝗻𝗮 𝗞𝗮𝗺𝗽𝗿𝗮𝗻𝗶

That's all we have for this week! Tell us how you feel by hit a reply or comment.

We love feedbacks 🫶

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