Big Tech Chases Big AI for Big Reasons

The capital-intensive battle to lead the generative artificial intelligence market is important enough for Alphabet, OpenAI, Meta and a few others, as it arguably creates a platform for the next era of computing and computing-based applications and business models. 

In fact, AI might be a somewhat-rare general-purpose technology that ultimately affects virtually the entire economy. 

But big hopes are accompanied by huge capex spending. 

source: Sherwood News 

And that big spending is chasing big potential. 

Generative AI is  "a really unusually large, maybe once-in-a-lifetime type of opportunity," according to Andy Jassy, Amazon CEO. 

"When we go through a curve like this, the risk of underinvesting is dramatically greater than the risk of overinvesting for us here,” said Sundar Pichai, Alphabet CEO. 

"This next generation of AI will reshape every software category and every business, including our own,” said Satya Nadella, Microsoft CEO. 

That won’t calm unease about the huge upsurge in capital spending to create and support large language models, but the huge potential is the driver. 

But the strategic implications also might be profound, as GenAI might be key to defending or extending digital real estate. In other words, GenAI possibly is about protecting platforms and ecosystems: keeping users engaged within the ecosystem. 

As with computing platform battles of the past (operating systems, hardware and application ecosystems),  generative AI is viewed as a key tool for protecting business moats around existing ecosystems. 

Beyond that, the heavy investments in generative and other forms of AI--though unsettling--are made not only to secure leadership of a platform that might drive the next era of computing and technology, but also might do so in large part because AI might reset expectations about the “cost of doing things,” as has tended to be the case for earlier general-purpose technologies. 

GPT	Key Innovation	Cost Reductions Produced
Steam Engine (18th century)	Mechanized power generation	- Reduced transportation costs (rail, shipping) - Lowered manufacturing costs through mechanization
Electricity (19th century)	Reliable, distributed power	- Reduced costs of lighting, heating, and powering factories - Enabled more efficient production processes
Computers (mid-20th century)	Automation of data processing	- Lowered costs of calculation, record-keeping, and data management - Improved productivity in administrative and technical tasks
Internet (late 20th century)	Communication and information access costs	- Drastically reduced communication costs - Enabled e-commerce, lowering retail and transaction costs
AI (21st century)	Intelligent data processing and automation	- Potential for reduced labor costs in repetitive or cognitive tasks - Lower costs in decision-making through better predictions and insights

Zoom Wants to Become a "Digital Twin Equipped With Your Institutional Knowledge"

Perplexity and OpenAI hope to use artificial intelligence to challenge Google for search leadership. So Zoom says it will use AI to challenge productivity suites and collaboration platform providers. 

Saying the company wants to become an “AI-first work platform for human connection” rather than a video collaboration tool is ambitious, but perhaps no more so than Perplexity or OpenAI challenging Google’s leadership of the search business. 

Absent the disruptive potential of AI, it might seem foolish to think about challenging Microsoft’s productivity suite position. But AI arguably changes the game.

Many users already have discovered that generative AI chatbots are, in fact, a substitute for traditional search. 

So Zoom might hope it can leverage AI to create a  “fully customizable digital twin equipped with your institutional knowledge.” 

It’s ambitious, audacious and risky. But that’s what general-purpose technologies are: platforms that can affect an entire economy. 

Domestication of plants	Neolithic agricultural revolution	9000-8000 BC
Domestication of animals	Neolithic agricultural revolution, working animals	8500-7500 BC
Smelting of ore	early metal tools	8000-7000 BC
Money	trade, record keeping	9000–6000 BC
Wheel	mechanization, potter's wheel	4000–3000 BC
Writing	trade, record keeping, poetry	3400-3200 BC
Bronze	tools and weapons	2800 BC
Iron	tools and weapons	1200 BC
Water wheel	inanimate power, mechanical systems	Early Middle Ages
Three-masted sailing ship	discovery of the New World, maritime trade, colonialism	15th century
Printing	knowledge economy, science education, financial credit	16th century
Factory system	Industrial Revolution, interchangeable parts	late 18th century
Steam Engine	Industrial Revolution, machine tools	late 18th century
Railways	suburbs, commuting, flexible location of factories	mid 19th century
Iron steamship	global agricultural trade, international tourism, dreadnought battleship	mid 19th century
Internal combustion engine	automobile, airplane, oil industry, mobile warfare	late 19th century
Electricity	centralized power generation, factory electrification, telegraphic communication	late 19th century
Automobile	suburbs, commuting, shopping centres, long-distance domestic tourism	20th century
Airplane	international tourism, international sports leagues, mobile warfare	20th century
Mass production	consumerism, growth of US economy, industrial warfare	20th century
Computer	Digital Revolution, Internet	20th century
Lean production	Growth of Japanese economy, agile software development	20th century
Internet	electronic business, crowdsourcing, social networking, information warfare	20th century
Biotechnology	genetically modified food, bioengineering, gene therapy	20th century
Nanotechnology	nanomaterials, nanomedicine, quantum dot solar cell, targeted cancer therapy	21st century