Web 3.0

A few years back, we heard a lot about Web 3.0 based on peer proof through blockchain technology. Currently, ICANN registers domain names. Instead, in Web 3.0, this function was to be managed by a decentralized community. It would verify domain transactions and the traffic passing through the network using proof-of-work (PoW) blockchains.

What was promised was user sovereignty. Still, Web 3.0 has witnessed a pause. It is not being talked about. It has taken a back seat.

There are some issues. There are technological hurdles. There are regulatory uncertainties. The technology is complex and is not scalable. It leads to poor user experience. It is not easy to deal with decentralized apps.

Setting up a domain is a daunting task. It requires outsourcing. Web 2.0 is user friendly.

Security and decentralization are talked about, but these come at a cost. There are slow transactions. There is intensive energy consumption. Decentralized nature causes regulatory issues. Despite promises of security, there are hacks. DeFi is vulnerable due to smart contracts.

Crypto boom and NFTS led to an interest in Web 3.0. However, the speculative bubble has burst.

It is too early to write off web.3.0. The principles on which it is based cannot be overlooked. It requires some key developments to move further — advances in blockchain technology, more efficient consensus mechanism, user friendly apps, lowering barrier to entry for non-technical users.

Web 3.0 can overcome current stagnation by suitable regulation and technological innovation.

Zoom

During Covid times, everyone was fond of using Zoom. However, after things have settled down, it has been realized that Zoom should be more than just a video call service and becomes an end-to-end communications platform with emphasis on AI assistance.

Zoom’s traction has increased by AI powering — it has garnered 7-million consumers worldwide for its Zoom Phone. There are other products such as Zoom Contact Centre and AI Companion.

Zoom Phone is a cloud business communication platform. It enables Wi-Fi phones, cellular data calls. One can switch from video to voice calls and from desktop to handphone. There are various other chat and call management tools.

AI Companion is generative AI assistant. It can summarize chats, give meeting transcripts, do language translations, compose emails, send calendar invites, generate post-call tasks for follow-up among other things. More than 5 lacs plus Zoom accounts have enabled AI Assistant since its September 2023 launch. In five months, it has generated 7.2 million meeting summaries.

India has two data centers of Zoom — Mumbai and Hyderabad. It has two technology centers — Bangalore and Chennai.

AI features are offered free to the customers. It empowers everyone.

Training Data for AI Models

LLMs are being trained by vast amounts of data and operate with lot of programming. In fact, human programmers create AI machines. Consequently, human errors and innate biases are seamlessly transferred to the machines and get manifested through AI actions and behaviour.

AI’s life blood is data. Data is the driving force behind its development and learning. ChatGPT was trained using 570 GB of text data, or around 300 billion words. DALL-E and Midjourney, two image-generating apps, employ a stable diffusion algorithm that is trained on 5.8 billion image-text pairs. We do not know what training data has been used by Google for Gemini. It could include trillions of pieces of text, images, videos and audio clips.

The data used by AI developers is sourced from high-quality academic papers, books, news articles, Wikipedia and filtered internet content to train the LLMs. The available high-quality data is not enough. Consequently, low-quality data from user generated texts (blog posts, social media posts, online comments) is also used. The low-quality data is perhaps more biased than the high-quality data. It might have illegal content as well. Apart from this, AI systems use simulated or synthetic data that is created by an AI model. Almost some 60 per cent data is likely to be synthetic by 2024, as against 1 per cent in 2021. The underlying programming for these simulations may introduce bias into the data.

If the data is not regularly updated, it becomes dated. Initially, ChatGPT’s data’s cut off was until 2021.

Add 10 Healthy Years to Your Life

There has been research on aging and longevity in bits and pieces, but of late, the world’s billionaires are pouring in money and deploying talent to extend human life.

Sam Altman of OpenAI is taking moonshot on reprogramming human body. He runs a side project called Retro Biosciences. His startup has an investment of $180 million. It has a goal of extending human life by 10 healthy years. He has teamed up with Betts-LaCroix who promotes hard science and deep biology through his non-profit organization called Health Extension Foundation.

Life extension may seem to be a quirky project but it is a part of Altman’s futuristic world view.

Is Silicon Valley over-reaching by trying to fix everything? Or is it that spirit of rugged and toughened fend-for-yourself attitude that motivates Altman to take both fusion energy and human longevity into his stride.

The live-longer time frame suggested by him is plausible.

Open AI’s headquarters are in San Francisco. Retro Biosciences is located 30 miles south of it. It is closer to Meta, Apple and Stanford than the golden city. Its ethos is ‘more pirate than navy.’ It has a warehouse like office desks are perched on a platform. The employees can peek through narrow windows up there. The ambiance stimulates people to move fast and break things. The labs at Retro are converted shipping containers with high end ventilation.

The whole project is divided into three buckets.

1. Autophagy. Our cells are being recycled to keep them healthy. This has the potential to become a quick fix for aging. Theoretically, the recycling can be tweaked with a pill. Rapamycin and Metformin (for kidney transplants and diabetes respectively) are existing medications closest to a pill approach. They can boost longevity. It has yet no direct drug that specifically addreses this cellular housekeeping.

2. Cellular reprogramming. This is a trendy idea. Old cells can be reprogrammed to a slightly younger state. Japanese stem cell researcher and Nobel laureate Shinya Yamanaka’s research talks of Yamanaka Factors that can do this reprogramming, but experimentally it is difficult to accomplish this. Actually, it is remodeling of cells — this can cause cancer and there could be other health issues. Betts-Lacroix advises a gradual approach. Extract cells from ears or knee joints. Reprogramme them partially to de-age. Put them back into people when they are safe enough for treatment. One can avoid a person to start with — just do cell extraction to do programming. If that helps hearing loss or joint mobility, Retro can venture further –try something more advanced.

3.Plasma therapy. No doubt, this sounds like a Dracula-like concept since it promises rejuvenation. Mice have been used for experimentation. Their blood plasma is diluted with Saline. (It is better than young blood transfusion). In aged mice it improves may age-related issues — reduction in inflammation, improvement of liver and muscle health and improvement in the formation of brain cells.

Some research at Retro suggests that the technique can work in non-rodents too.

The life extension mission is a gargantuan mission. Both co-founders meet once a week. They are the Board now. In this longevity race, other competitors of Altman are Bezos (Amazon), Thiel and other billionaires. Bezo’s lab is San Diego. Thiel wants his body to be cryogenically preserved when he dies. It can be brought back to life later. He also believes that we can escape the velocity of death someday soon. German billionaire Angermayer is developing pills for improving aging. The pills include those that can keep ovaries younger so as to prolong the fertility window. Betts-LaCroix believes Retro is taking a moral call, rather than developing just a business model.

Pocket FM and Kuku FM

In India and elsewhere, there is a growing non-music audio market consisting of audiobooks, podcasts and audio series. Here two startups Pocket FM and KuKu FM are in audio entertainment segment.

Pocket FM offers bite-sized episodes of audio stories and novels in regional languages. It wants to deepen push into the US and expand into Europe and LATAM market in 2024. It follows a freemium model where the revenues are generated through both subscriptions and advertising. There are micro-transactions — a user can unlock a chapter of a novel for as low as Rs.9. In 2023, there were 20 million transactions and 75 billion of minutes of streaming worldwide.

KuKu FM largely focuses on audiobooks and podcasts in regional languages. It has signed an exclusive contract licensing deal with Storytel (Stockholm-based). It will offer translations of English books in regional languages.

Suleyman Joins Microsoft

Mustafa Suleyman, as we know, was the co-founder of AI research lab DeepMind. DeepMind since then has been acquired by Google in 2014. He continued to work in DeepMind until 2022. It wanted to create AI that will not veer into racist, sexist or violent behaviour. He left DeepMind in 2022 to cofound Inflection AI, an ML and generative AI company. Reid Hoffman (Greylock’s) too was a co-founder of Inflection AI. In 2023, Inflection AI launched a chatbot named ‘Pi’.

Microsoft has now appointed Suleyman (2024) as EVP and CEO of its newly created consumer AI unit, Microsoft AI. Several members of Inflection AI’s team have been appointed to the division, including co-founder Karen Simonyan.

He has co-written a book, The Coming Wave, that examines AI’s promise and the need to limit its potential perils.

The companies in AI space, namely Google, Microsoft and Apple are forming alliances so as to capitalize on generative AI. The idea is to generate revenue by marketing suitable consumer products and capture the market share. Each company does not have all the ingredients which can be assembled together to capitalize on generative AI. The ingredients are computing power, top-of-the-line AI models, trustworthy products and ways of getting them to people. The companies continue to search worldwide for talent and promising startups.

Google’s products have serious errors and biases. Microsoft has not been skilled at building exciting consumer products apart from video games. Apple is years behind in AI.

Big Tech is incapable of innovating the entire generative AI ecosystem single handedly.

Microsoft has infused AI into Bing search engine, Windows, Office and other products such as digital assistants under the Copilot brand.

This is the reason why Suleyman has been roped in. They went to craft in a true end-to-end product experience. Suleyman compares this to sculpting — recognizing when a piece of technology is ready and how to dress the experience that it becomes accessible and trusted.

Is Suleyman the right person to do this? He has developed a chatbot called Pi, which attracted a million active users. However, his startup Inflection never found a business case.

High Bitcoin Prices

Bitcoin prices reached a high $73000 mark. The market anticipates a high demand, while the supply is limited. It is all because of the halving event which occurs once every four years, The event is steeped into the design and philosophy of scarcity. Satoshi Nakamoto, the creator of Bitcoin, designed the crypto to have a finite supply of 21 million coins. The issuance of new coins is reduced. Halving is significant as it cuts by half the rewards the miners receive while validating the transactions. It reduces the rate at which Bitcoins are created, suppressing the supply of new Bitcoins. In 2009, miners received 50 Bitcoins for every 10 minutes. There were three halving. They now receive 6.25 Bitcoins every 10 minutes.

Halving occurs after mining 2,10,000 blocks. Mining is the process of making computer hardware do mathematical calculations for Bitcoin network to confirm transactions and increase security. In April 24. there will be next halving. The block reward will be restricted to 3.12 Bitcoins for every 10 minutes of mining.

Bitcoin pricing, among other things, is scarcity driven. By the year end (2024), the prices may hit $150,000 and $250,000 in 2025.

As value increases, despite reduction in rewards, profitability of miners may not get affected. Miners may have to reduce power consumption and may have to improve hardware efficiency.

The Fall of Credit Suisse

UBS, the bank which took over the collapsed Credit Suisse, has a balance sheet worth $1.695 trillion. It overshadows the Switzerland’s home economy. It is twice the size of the GDP of home country. HSBC’s balance sheet in terms of leverage of exposure is worth 83 per cent of UK’s GDP. BNP Paribas is equal to 72 per cent of France’s GDP. At the same time, JPMorgan Chase, the world’s largest bank is just 17 per cent of US GDP.

UBS should not be in distress, as it would burden Switzerland unbearably. There are three other systematically important Swiss banks — their sizes range from 15 per cent to 37 per cent of GDP.

Credit Suisse failed because of its top management (board and executives). There were years of bad strategy and faulty management decisions. The executives kept changing but there were new scandals and losses with each new batch of executives. Far too much capital, and far too less return dragged it down. Discipline and risk-return were ignored.

The regulator conducted several investigations and issued several reprimands. There were a few criminal charges. There was action against the staff. As the whole banking sector would be affected adversely, regulators do not name and shame people and institutions. There are punitive fines and dressing down in regulator’s offices.

The gradual collapse could be seen coming, but regulator cannot put restrictions. The intervention comes when the institution is on the brink of collapse. Despite being aware about the shortcomings, the regulator could not direct the bank on the right path. The management refused to face the truth.

There was loss of liquidity at Credit Suisse. Depositors fled. There were collaterals to raise funding. It was not possible to transfer the collaterals from the group holding company legally to its overseas units.

The US, UK and Europe have realized this issue and have asked the banks there to use liquidity facilities to prevent the speedy runs on banks in modern times.

Blackwell Chips

The chip making company Nvidia is now the third most valuable company in the US, behind only Microsoft and Apple. This Santa Clara-based chip maker has earned the title of the world’s most valuable chip maker, eclipsing the celebrated competitors such as Intel and AMD.

There is an AI boom and there is edge computing. The firms are moving from exploration to deployment. AI computing basically requires high performance graphical processing units (GPUs). Traditionally computers used central processing units (CPUs). Intel and AMD dominated the CPU market. GPUs are relatively new additions to the computer hardware market. These were initially sold as cards that were plugged into a personal computer to add computing power to an Intel or AMD CPU.

The graphics chips can handle the kind of surge in computing power that is needed in high-end graphics for gaming or animation applications. Standard processors cannot handle this surge. AI applications too demand high computing power. In their backend hardware, these apps are becoming GPU-heavy.

In most advanced systems for training generative AI models, for every one CPU, at least half a dozen GPUs are deployed. The equation when GPUs were just an addition to CPU has completely changed. This lead will be maintained by the GPUs in the near future.

Nvidia first popularised the term GPU in 1999. Its chip was called GeForce256. This chip was coveted for graphics. These chips were more expensive than most CPUS (on a per unit basis). It resulted into better margins. TSMC, the Taiwan-based foundry specialist is the important player in the backend semiconductor business. Intel, AMD, Samsung and Qualcomm are the front-end players.

The most popular AI chip of Nvidia is H100, which was launched in 2023. It has 80 billion transistors. The company has now introduced B200 Blackwell, the new chip. It has 208 billion transistors. It can do some computational tasks 30 times faster than the current blockbuster H100. The new chip with its more computational power and optimised power consumption will strengthen the dominance of Nvidia in the niche space. It is twice as powerful while training AI models, and five times more capable while inferencing. (the inferencing is done by models such as Gemini, or ChatGPT while tackling queries and generating response).

A training GPT model (which powered ChatGPT) had 1.8 trillion parameters and 8000 Hopper GPUs. It consumed 15 MW of electricity. The new 2000 Blackwells can do the job while consuming just four MW of power.

Major buyers such as Google, Amazon, Microsoft and OpenAI are expected to use the new chip in their cloud-computing service and in their AI products.

Nvidia is ahead in AI race because of its hardware as well as its proprietary software that facilities the leverage of its GPU hardware for AI apps. Nvidia also has developed systems that back its processors and software to run all of this. It is thus a full-stack solution company.

Possible Tie-up of Apple and Google

Apple and Google are reported to be in talks for empowering Apple’s iPhones with license to use its LLM Gemini, a generative AI model. Apple has reported to have discussions even with OpenAI for using its model on its iPhone.

Since long, Google was being paid billions of dollars by Apple per year to make Google Search a default option on Apple phones and other devices. If the present Gemini deal comes to fruition, Apple will have to pay Google substantial fees per year. Though Apple itself is fiddling with AI research (Ajax), the technology remains far inferior to the tools developed by Google and OpenAI.

The terms of the agreement have not been finalized yet.

Gemini will be on firm foothold if the deal materializes, as it will have access to more than 2 billion devices in active use. Samsung has already rolled out new smartphones infused with AI features powered by Gemini.