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BLUECHIPINVESTMENT | TechnologySurvival of the fastestWith the arrival of Artificial Intelligence into the mainstream world, we find ourselves at apoint of optimism over the future in this cycle of technology innovation.Remember Netscape Navigator? The company was thedominant web browser and search engine in the 1990s,later displaced by Google, Microsoft, Apple and Amazonas the kingpins of the Internet age. At the height ofNetscape’s success, Google was a one-year-old startup, Microsoftwas just releasing Windows 2000 – its latest operating systemthat you could buy in a box set, while Apple was making goodlookingdesktops and Amazon was an emerging online bookstore.Netscape was seen by investors as the access point to theboundless opportunities that the Internet held for the futureof business, causing the share price to soar after its IPO in 1995,even though it barely made a profit on meagre sales. What thecompany did to generate those sales did not matter to investors asthey bought into the hope of future earnings. As the San FranciscoChronicle reported at the time:“It’s more likely that investors believe the myriad alliancesNetscape has struck with other technology companies willenable it to set the tone for developing business, banking andentertainment on the World Wide Web. The bottom line is that itdoesn’t matter that Netscape is still a puny company on paper.The future is what counts, and optimism over the future has juicedthe stocks of most Internet-related companies, not just Netscape.” 1The public launch of ChatGPT in 2022 created a wave ofexcitement as the world tried to digest this new wave technologythat showed the potential to answer complex questions like ahuman would. This also caused an increased level of anxiety asthe concept of machines taking our jobs was suddenly morerealistic than a Hollywood film plot. Elon Musk was at painsto point out at the time that there was a myriad of unintendedconsequences that followed the launch of this technology andthat serious controls were needed. The AI machine, however, hadbeen built and unleashed on the world.The emergence of AIAI has been in existence as a field of research since the 1950s.Much of this body of work has already been integrated into manyaspects of our daily lives as well as the economy. For example,autonomous robots building cars are controlled by AI systems,while the predictive text when typing a phone message hasbeen around for almost a decade. The step change with themost recent iteration of AI relates to the rationalisation andreasoning capabilities of the large language models (LLMs) thatunderpin the now common ChatGPT and Gemini applicationsthat you can access on your phone.These models are like a super-smart colleague that you can talkto, just like you would a person. You can ask anything – questions,help with writing, explanations or even just to chat – and itresponds in a way that sounds natural. It doesn’t have feelings, butit’s been trained to understand language by reading a huge volumeof Internet-sourced books, articles and conversations. It doesn’t“think” like a human; it gives you helpful or interesting answersbased on what it’s learned. (This comment was in fact written byChatGPT.)The range of future uses for AI are impossible to predict26 www.bluechipdigital.co.za
INVESTMENT | TechnologyBLUECHIPbut are likely to include services that complete mundane dailytasks like restocking your fridge to more complex tasks such asnegotiating legal agreements for the sale of a property. In business,AI management teams could form the nucleus of a companydirecting and organising resource allocation. These tools couldsolve hugely complex logistical or optimisation challenges in ourelectrical grid or traffic management systems to boost efficiencyand productivity. These ideas may sound far-fetched, but thisis exactly where LLMs are being actively applied today, and weare likely to see the introduction of these services in the not-sodistantfuture.The drivers of AI developmentThe key parties driving the development of AI technology and itsprogression into real world commercial applications are broadlygrouped as follows:Infrastructure. Manufacturers of graphics processing units(GPUs) train and run the most advanced models, eg Nvidia. Thesechips are highly specialised and hard to replicate, with only ahandful of companies providing them at this stage.Hyperscalers. These are large technology companies likeMeta, Microsoft and Alphabet that have leveraged the scale oftheir platform businesses and balance sheets to develop variousservices and applications related to AI technology. The likes ofAlphabet have chosen to internally develop this capability (egGemini), whereas Microsoft has formed strategic partnershipswith AI leaders like OpenAI to secure its spot as the frontier ofthe market.Other downstream providers. These are businesses that haveestablished teams of experts developing inhouse AI capabilitiesto avoid being behind the technology curve (banks and insurers)or venture capitalists funding early startups to set up the “newnew thing”. 2The stakes of participation are high, requiring cutting-edgecomputing power, significant electricity consumption, accessto vast datasets and the technical expertise needed to train themodels. This has narrowed the field of companies pursuingAI technology to a select group, who have deployed largeamounts of capital to invest in AI-related initiatives.Yet, AI is increasingly viewed as essential for survival acrossbusiness and government, seen as a critical investment to maintaina competitive edge or to avoid obsolescence. This has fuelled analmost “sky-is-the-limit” expectation of what companies are willingto pay to stay at the forefront of AI, unlocking vast potential forfuture revenue streams tied to AI-related services owned by thecompanies that hold the key to technology.Share prices have reflected this enthusiasm as the marketincreases its revenue expectations for this small cohort of stocks,in other words, rewarding AI leaders for the high level of capitalexpenditure on AI.The winners today may not be the winners of tomorrowThe AI infrastructure stocks like Nvidia have been early winners,enjoying extraordinary profits as demand for their chips has risenwith the need for additional computing speed and stock-pilingefforts by Big Tech, while competition has been almost nonexistentand supply is constrained.However, the winning business model for service providerslike Microsoft, Meta and Alphabet has yet to emerge. Despite this,their stock prices reflect a scenario in which they win the AI raceand successfully translate this position into higher earnings – anoutcome that is far from certain. For example, it remains unclearhow Microsoft will integrate AI into its existing services, a processthat could take years of trial and error. This uncertainty raisesquestions about Microsoft’s future business model, with a widerange of possible outcomes – ranging from immense success(Microsoft Azure cloud service) to obsolescence or something inbetween with slower- than-expected earnings growth.Another threat is the emergence of innovative technologieslike DeepSeek that can disrupt the status quo. DeepSeek is aone-year-old Chinese startup that recently showed the worldthere are faster, cheaper ways to compete. This not only reducesthe amount of computing power needed to build and run AImodels (less chips and data centres) but also weakens thecontrol that Big Tech has over cutting-edge AI models. Thereare questions about DeepSeek’s merit, sustainability andsecurity, but that misses the point:• Its emergence shows the value that AI potentially holds, witha billionaire hedge fund manager from China betting hisfortune on AI. Other tech billionaires like Eric Schmidt (Google)are doing the same with startups like Anthropic.• It reminds us that we are still in the exploratory disruptivestage of the AI lifecycle, with potentially no clear winnersidentified yet. Recall the earlier example of Netscape, whoalong with a myriad of other early innovators of the Internetdisappeared, later to be replaced by Google, Amazon andFacebook, who emerged much later in the cycle as winners.They then developed platform business models that no-one,not even their founders, imagined in early infancy.Hence, history demonstrates that the current AI winners today maynot be the AI winners of tomorrow. For example, does Alphabetget replaced by a superior alternative to Google Search or doeswww.bluechipdigital.co.za 27
