Poisoned Apples, Artificial Intelligence and Virtual Theatres / Hong Kong Radio 3
Does Apple tech get viruses like their PC cousins was where Phil Whelan of Hong Kong Radio 3 and I started this weeks chat, with the answer being yes, but in smaller numbers than their relatives, because the tight ecosystem makes it far harder for the perpetrators to get into a Mac piece of tech.
We then turned our attention to some of 2015’s more obscure but nevertheless significant tech occurrences like Tesla’s recent software upgrade to its cars that changed the way the car performs and turned them into a semi autonomous vehicle – up until now the only way to get these changes was significant under the hood time and effort or a new car. The rocket take off and landing by Jim Bezos of Amazon fame was another milestone, making travel into low orbit and return to the earth ever more possible.
Artificial Intelligence (AI) was next on the agenda as we explored Elon Musk and his billionaire tech mates founding an institute to ensure that AI is developed for benevolent and humanitarian purposes and not used for evil a noble cause and worth pursuing, but I’m not sure all the “bad people” are really going to care.
We finished up this week exploring the near future of virtual reality concerts and theatre.
A great chat as always, so have a listen now (minutes seconds)
Frequently Asked Questions
Q: What were the most important AI signals visible in late 2015, and how have they played out?
The AI signals that were most significant in late 2015 included: AlphaGo’s demonstration of deep learning capability at human level in Go, which arrived in 2016 and proved more significant than most commentators understood at the time — not because Go is important but because the approach (reinforcement learning from self-play) generalised to other domains; the rapid improvement in natural language processing demonstrated by neural machine translation, which began producing near-human quality translation for common language pairs; and the emergence of generative adversarial networks as a research tool for synthetic image generation, which would later become the foundation for the image generation revolution of 2022-2024. Looking back from 2026, the 2015 signals were clear but the timeline was underestimated by most observers — the capabilities visible as research demonstrations in 2015 took seven to ten years to reach consumer deployment at scale.
Q: What did the early virtual reality platform launches of 2015-2016 (Oculus, HTC Vive, PlayStation VR) actually deliver, and where is VR in 2026?
The 2015-2016 VR platform generation delivered proof of concept for immersive experience but fell significantly short of the mainstream adoption that boosters predicted: the hardware remained expensive, heavy, and tethered; the motion sickness problem proved harder to solve than the industry acknowledged; the content ecosystem was thin; and the social isolation of solo VR experience limited its appeal as a primary entertainment medium. The 2026 VR/AR landscape looks meaningfully different from the 2015 predictions: standalone headsets have made the hardware accessible; the Vision Pro and similar devices have moved toward spatial computing rather than isolated VR; and the most successful applications of immersive technology have been enterprise (training, design visualisation, remote collaboration) and fitness/gaming rather than the social virtual world predicted by Meta’s pivot. The metaverse as a consumer platform has not arrived at the scale predicted.
Q: What does the AI and VR signal landscape of 2015-2026 reveal about how to interpret technology demonstrations?
The 2015-2026 decade in AI and VR reveals consistent patterns in technology signal interpretation: research demonstrations typically lead commercial deployment by five to ten years, and the applications that eventually dominate are rarely the ones that receive the most attention during the demonstration phase; the technology that attracts the most investment and media attention in any given year is not necessarily the technology that will have the largest impact — the transformer architecture that underlies the current AI revolution was published in 2017 and attracted relatively little public attention compared to VR; and the compounding nature of AI improvement means that the capabilities of 2026 would have seemed impossible to 2015 observers, which should inform humility about 2026 predictions for 2035. Reading technology signals well requires attention to underlying capability improvements rather than surface-level product announcements.
Q: How can I book Morris Misel for an AI, virtual reality, or emerging technology futures keynote?
Contact the booking team at morrismisel.com/event-organisers.
Does Apple tech get viruses like their PC cousins was where Phil Whelan of Hong Kong Radio 3 and I started this weeks chat, with the answer being yes, but in smaller numbers than their relatives, because the tight ecosystem makes it far harder for the perpetrators to get into a M.
The impact of Poisoned Apples, Artificial Intelligence and Virtual goes beyond process efficiency. It reshapes roles, redistributes decision-making authority, and changes the human skills that matter most. Leaders who understand these second and third-order consequences early have a real advantage over those waiting for the technology to stabilise before engaging.
The most important question is not whether Poisoned Apples, Artificial Intelligence and Virtual will matter, but how quickly it will matter in your specific context. Leaders benefit most from mapping the ripple effects early — not just the direct impact but the second and third-order consequences that arrive later and hit harder. That is the practical work of foresight.
