Is this like the CEO of McDonald’s suggesting that cooking skills are no longer necessary?
At the recent World Global Summit (WGS), an annual gathering uniting leaders across industries to discuss global policies, Nvidia CEO Jensen Huang shared a bold claim on the significance of coding in the age of artificial intelligence (AI).
In the post, Nvidia’s CEO asserts that the rapid advancements in AI models will enable anybody to become programmers. Huang foresees a future where programmers won’t have to master Python, Java, or other coding languages; proficiency in natural language processing will be enough.
For those intrigued by the full discussion, feel free to watch it here.
It’s easy to take this claim at face value, but upon closer inspection and a little digging on the web, online discussions suggest that this claim is motivated by Huang’s intention to dominate the AI server chip industry.
This post by user Loshan1212 highlights that Huang’s recent claim is primarily intended to excite investors about investing in Nvidia chips, as these chips currently represent the top choice for powering AI technologies.
Meanwhile, Nimblegeek playfully teases Huang for underestimating the significance of coding in software development.
Another intriguing perspective that caught my attention is a comment by USAFRet in a Tom’s Hardware article titled “Jensen Huang says kids shouldn’t learn to codeâthey should leave it to AI.”
This observation is spot-on. The core of successful natural language processing (NLP) utilization lies in grasping logic, a skill that can be honed through coding. Coding empowers us to devise effective problem-solving strategies.
This isn’t the only unconventional claim Huang has given in recent months. Last Oct. 16, 2023, during an interview with “Acquired,” a podcast featuring the tales of thriving and up-and-coming companies, Huang expressed that if he could turn back time, he wouldn’t have started his own company.
The Nvidia CEO goes on to share the burden and sadness that come along with starting a company. The people who rely on him both for their career and livelihood. It’s a pressure that he didn’t envision when he was starting.
Huang assumed that for an entrepreneur, having a vision and determination are enough, overlooking the importance of empathetic qualities.
Contrary to the backlash following his recent statement, this video garnered him admiration from viewers. They expressed how truly humbling it must have been for Huang to serve as the CEO of the world’s third-wealthiest company.
In the comments, some even cited the 2023 survey by Blind, a social media platform for corporate professionals, indicating that Huang is favored by 96% of his company, the highest CEO approval rating among all companies in the market.
Amidst the widespread praise for the Nvidia co-founder, what prompted the recent criticism? Is Nvidia attempting to monopolize the GPU market? Is discouraging people from pursuing careers in tech all part of the plan?
Let’s crack the code!
- What is Low-Code, No-Code
- So, What? The Rise of a New Monopolist
- Now, Whatâs in it for u+
Low-Code, No-Code
Being deeply involved in tech, Huang’s statement strikes a chord with me.
We’ve all witnessed significant progress in the past six months, and frankly, these advancements may render certain coding tasks obsolete. From my perspective, Huang is anticipating the long-term effects of low-code and no-code on various industriesânot just in tech. This straightforward and innovative software development approach will empower us to enhance our creations and create more.
But, what is “low-code, no-code,” and why is it so important?
Low-code and no-code developments have gained prominence in recent years as quick and easy approaches to app development.
Low-code involves using readily available tools with minimal hand-coding, while no-code platforms offer pre-made designs that users can customize without coding.
A great example of this software is Zapier, a platform that provides web application integrations for automated workflows. Zapier enables users to combine applications swiftly, allowing them to utilize multiple functions simultaneously. Another example is Airtable, a cloud collaboration service with the features of a database but applied to a spreadsheet. Airtable enables users to build databases effortlessly, eliminating the need for setting up Excel spreadsheets. Both these applications help users create products at scale by doing the hard work for them. Zapier and Airtable had already taken care of the hard coding and now, we simply choose a template that works for us.
These techniques have revolutionized software development by offering visual interfaces that allow users to visualize their projects. This simplifies the app creation process, cutting down the time and effort needed compared to traditional coding where everything must be built from the ground up.
Here’s a quick overview of the difference between the two.
Although they differ in most aspects of coding, it’s important to note that their main goal is to make coding quick, easy, and most importantlyâaccessible.
But, what does low-code, no-code have to do with Jensen Huang’s claim?
The Rise of a New Monopolist
On Feb. 14, 2024, Nvidia was revealed to have exceeded Alphabet; Google’s parent company, in market capitalization.
Nvidia has reached a market value of $1.83 trillion, closely followed by Alphabet at $1.82 trillion. This shift occurred shortly after Nvidia surpassed Amazon in market value.
Currently, Nvidia ranks as the third largest U.S. company, trailing behind Apple and Microsoft. These milestones are all intricately tied to the emergence of AI.
Before the recent surge in AI technology, Nvidia primarily focused on supplying consumer graphics processors to PC manufacturers for building gaming computersâa less profitable market than AI.
This is because Nvidia’s AI server chips come with a hefty price tag ranging from $15,000 to $40,000, the most expensive in the market. With industry giants like OpenAI, Meta, Google, and Amazon using these chips to host their large language models (LLMs), it is foreseeable that Nvidia will maintain its dominant position or even surpass Apple and Microsoft.
With the increasing adoption of AI and its applications to low-code, no-code software, the demand for these server chips rises.
While AI automation provides convenience through speed and simplicity, proficiency in understanding logic is still the key to unlocking its full potential and advantages.
Now, What’s in it for uâș
I know, Nvidia is dominating the industry right now, BUT, earlier this week, Groq, a new server chip designed to handle and manipulate human language data, entered the market.
This chip champions a new processor called Language Processing Unit (LPU). It is not a variation of the more known processor Graphics Processing Units (GPUs) rather, it’s a new technology intended for LLM and deep learning use. A novel science that challenges Nvidia.
With this new technology entering the playing field, we can expect that products that share the same use cases will speed up their developments, or lower their prices. This shift will emphasize the value of a decentralized marketâaligned with the promise of open-source models.
With all this being said, should we stop learning how to code?
Understanding coding is key to maximizing the potential of AI tools. This proficiency allows us to tailor and optimize models for our specific needs.
Uncovering the perfect low-code or no-code software that resonates with your vision is key in today’s market. Identify the most suitable option and then innovate upon it.
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