073 | TeslaGPT?

Friday Funtime

This is Brainyacts. Its like the WD-40 of Generative AI, eliminating the creaks and groans of your learning process and leaving you with a smooth and slick understanding.

Let’s keep growin’.

A special welcome 👋 to my NEW SUBSCRIBERS! 

To read previous posts, go here.

In this edition we will

1. consider a sleeper in the GenAI race to win the market

2. dig into two critical roles in legal AI

3. learn that NYC public school are embracing ChatGPT

4. test if a state legislative bill can be written by AI

5. read how a huge telecom company is axing 50K jobs due to AI

6. meet the Chinese ChatGPT called Ernie

TeslaGPT: The AI Winner?

Tesla: The Unrecognized Force in Generative AI

When people think about leading companies in the AI industry, it's easy for names like Google, OpenAI, and Microsoft to spring to mind. These giants have made considerable strides in the GenAI sector, but there's one company that tends to be overlooked in this conversation: Tesla. Though primarily known for their groundbreaking electric vehicles and renewable energy technology, Tesla possesses an impressive artificial intelligence repertoire that is not to be underestimated.

Tesla's Advanced AI Infrastructure

Most people know Tesla for its pioneering efforts in the electric vehicle market, with its Self-Driving Technology being one of the most remarkable features. However, this same technology provides Tesla with a robust foundation for AI development. Tesla's Autopilot system is built upon sophisticated machine learning models that interpret complex data from a myriad of sensors. This data is then used to make decisions in real-time – an attribute directly transferrable to generative AI.

For some insight into Tesla AI supercomputer DOJO, watch this video:

One cannot overstate the value of Tesla's real-world data collection. The millions of Tesla vehicles on the road continually supply the company with a wealth of data, an invaluable resource for any AI project. Furthermore, the hardware in every Tesla vehicle, designed for the real-time processing needed for autonomous driving, can also serve as a powerful engine for other AI tasks.

Potential to Compete with Existing AI Models

With the AI infrastructure in place, Tesla is uniquely positioned to leverage this technology to compete with established AI platforms, such as Bing Chat and ChatGPT. Tesla's Autopilot system is fundamentally a deep learning system that can be repurposed or retrained to perform different tasks. Similar to how ChatGPT was trained on a vast amount of internet text to generate human-like text, Tesla can use its massive collection of data to train its AI for various applications, including generative tasks.

From a talent perspective, Tesla has one of the best teams in the AI industry, capable of driving innovation in unexpected areas. With a reputation for disruption and a culture of innovation, Tesla has the potential to redefine the AI landscape just as it has redefined the automotive industry.

Relevance in an AI-Driven Future

In an era where AI is predicted to play an even larger role in everyday life, Tesla's capacity to become a significant player in the AI space should not be underestimated. It is a company that has already proven itself capable of pioneering and disrupting traditional industries.

How Elon Musk Has Distinct Assets or Weapons in the War to Win the Generative AI Market

Elon Musk is not only the CEO of Tesla and Twitter, but also the founder of several other ventures, such as SpaceX, Neuralink, The Boring Company, and X.AI. These ventures give him distinct assets or weapons in the war to win the generative AI market, which is expected to be worth $51.8 billion by 2028.

Twitter Data

With Musk owning Twitter, he has the ability to access is vast repository of user data to train an LLM on - just like OpenAI and Microsoft have - and now Musk wants to charge them for it. He gets it for free. This is a distinct advantage and while Microsoft has LinkedIn, the nature of conversation and discourse on Twitter is more varied and extensive, potentially offering richer data for training AI. Twitter is a global platform with diverse users sharing thoughts on everything from the mundane details of their day to complex geopolitical discussions. This myriad of topics, emotions, styles, and languages is a vast playground for AI training.

Elon’s Own Twitter Account

Musk’s Twitter account is one of his most powerful weapons in the generative AI market. With over 100 million followers, he can reach a massive audience and influence public opinion on various topics, including AI. He can also use his Twitter account to promote his own products and services, such as Tesla and X.AI, or to criticize his competitors, such as OpenAI and ChatGPT. Moreover, he can use his Twitter account to collect data for training his generative AI models, as he reportedly plans to do with X.AI.

Tesla’s DOJO and Data

As mentioned above, Tesla’s DOJO and data are another set of weapons that Musk has in the generative AI market. DOJO is a neural network training computer optimized for video, which Musk intends to use for self-driving and other projects. DOJO could potentially rival other large language models like ChatGPT in terms of performance and scalability. Tesla’s data is also a valuable asset for generative AI, as it consists of billions of miles of real-world driving data collected from its fleet of vehicles. This data could be used to train generative AI models for various purposes, such as creating realistic simulations, generating personalized recommendations, or enhancing customer service.

Starlink Network

Starlink network is a fourth weapon that Musk has in the generative AI market. Starlink is a satellite internet constellation that aims to provide high-speed broadband access to anywhere on Earth. Starlink could enable Musk to distribute his generative AI products and services to a global market, especially in areas where internet access is limited or unreliable. Starlink could also provide Musk with more data for training his generative AI models, as he plans to run a full dogecoin node on Starlink.

X.AI Start-Up

X.AI start-up is a fifth weapon that Musk has in the generative AI market. X.AI is a new artificial intelligence start-up that Musk launched in March 2023 to compete with OpenAI and ChatGPT. X.AI aims to build a large language model that can ingest enormous amounts of content and produce humanlike writing or realistic imagery. X.AI has already hired some top AI engineers from DeepMind and OpenAI, and has secured thousands of high-powered GPU processors from Nvidia. X.AI could potentially challenge the dominance of OpenAI and ChatGPT in the generative AI market.

FREE 5-day email course.

🆓 ⭐️ FYI I built this for anyone brand new to ChatGPT

• Beginners Introduction to ChatGPT
• 10X Your Productivity with ChatGPT

Sign up here: https://brainyacts.joshkubicki.com/course

Tool you can Use: Data Analysts & Data Scientists

Many legal teams (In-house and law firms) have already hired or are looking to (via consultant or employee) someone who can help with data and AI. These are relatively new roles in the legal field and I hear often that most folks don’t really understand what they do or how they are different.

Let’s change that.

Relevance to Legal Services

With the rapid digitization of legal information, there's an increasing amount of data being generated, from court cases, contracts, legal precedents, client information, and more. This is where both data analysts and data scientists become essential.

A data analyst in a legal team might help make sense of patterns in case data, like identifying what types of cases a firm wins most often, or identifying trends in judicial decisions. This can inform strategies and decision-making processes.

Data scientists, on the other hand, can be instrumental in developing AI tools that automate certain aspects of legal work, like contract analysis or legal research. They could, for example, help create an AI model that understands the language of legal contracts and can flag potential issues.

Understanding the difference between these roles is important as legal firms increasingly look to leverage AI. Depending on a firm's specific needs, they might benefit more from the interpretative skills of a data analyst, or the predictive modeling skills of a data scientist. Or they might need a combination of both.

Here are two terrific videos from Sundas Khalid, Google’s principal analytics lead is taking you to data-science school. 

The first one explains what a Data Analyst is, does, and how to become one.

The second one explains the difference and similarities between both roles.

News you can Use: 

NYC Schools Reboot AI: ChatGPT Returns with a New Learning Curve

New York City public schools are ready to engage with ChatGPT, after a previous ban. With individual schools able to request access, a measured approach towards integrating this technology has been adopted, aiming to harness AI's potential while minimizing its risks.

Plans to provide teachers with AI toolkits and establish an AI research repository have been announced by Schools Chancellor David Banks, with only 36 schools so far requesting access. The new curriculum includes activities to help students understand AI and its societal implications. In light of this cautious embrace, Banks envisions AI not only becoming a part of classroom learning but also aiding in administrative tasks.

New York State Assemblyman Uses AI to Draft a Bill

Telecom Giant BT's Massive Reshaping: 55,000 Jobs Shed by 2030 with AI Driving the Future

In an audacious move signaling the transformative power of new technologies, BT, the UK's largest broadband and mobile provider, is set to streamline its operations and cut a staggering 55,000 jobs by the end of the decade. As the telecom giant embarks on a path to become a "leaner business with a brighter future," artificial intelligence, notably generative AI like ChatGPT, is set to play a significant role in revolutionising customer service and network maintenance. This bold transformation, driven by AI advancements and a shifting focus from copper to fibre networks, is a profound indicator of the evolution of the telecom sector and the implications it has for the workforce.

News you can Lose: 

China’s ChatGPT, Called Ernie

DISCLAIMER: None of this is legal advice. This newsletter is strictly educational and is not legal advice or a solicitation to buy or sell any assets or to make any legal decisions. Please /be careful and do your own research.8