What to watch in AI
https://www.generalist.com/briefing/what-to-watch-in-ai
- Copilot for everything. AI is already streamlining illustration, writing, and coding. It may soon become an assistant for all knowledge workers. In the future, we may have versions of GitHub’s “Copilot” feature for lawyers, financial analysts, architects, and beyond.
- Tracking value accrual. As AI startups often rely on publicly available models like GPT-3 or Codex, some question their defensibility. The fundamental question centers around value accrual. Will applications that leverage GPT-3 successfully capture value? Or will it accrue to the infrastructural layer?
- Beyond words and images. GPT-3 and DALLE-2 have attracted deserved attention for their ability to automate text and image creation. The most impactful uses of AI may come from the life sciences, though. AI can be used to design better pharmaceuticals or run more efficient clinical trials.
- Improving interfaces. Interactions with AI typically take the form of a basic text box in which a user enters a “prompt.” While simple to use, greater control may be needed to unlock the technology’s power. The challenge will be to enable this potential without introducing needless complexity. Applications will need smooth, creative interfaces to thrive.
- Addressing the labor shortage. Skilled laborers are in short supply as society’s need increases. For example, while demand for skilled welders increases by 4% per year, supply declines by 7%. AI-powered robots may be part of the solution, automating welding, construction, and other manual tasks.
Trend: The elevation of human work
In the world we actually see evolving today, new AI tools effectively democratize facility and efficiency in unprecedented ways. In doing so, they’re empowering individual professionals to achieve new productivity levels and society to achieve gains that may exceed those unleashed by the Industrial Revolution. Not only that, but people will also find their jobs more engaging and fulfilling because they’ll have more time to focus on the most creative, strategic, and novel aspects of them.
This future is here. There will be an AI amplifying tool for every major profession within five years. These tools can catalyze human excellence across occupations – right brain, left brain, and any brain.
– Reid Hoffman, cofounder at Greylock, and Saam Motamedi, partner at Greylock
Trend: Collaborative interfaces
Everyone with internet access will very soon be indirectly using large language models in daily tasks. At a minimum, search will be disrupted unrecognizably, delivering answers and summaries on demand. We should also see LLM-based tools designed for more mastery and deeper interaction. Creatives already want generated images to be manipulable in structure, and workers want trustworthy output without hallucinations. Many might like their AI assistants to be educated with specific knowledge. These are the sophisticated “bicycles for the mind” that will unlock productivity for knowledge workers.
Early ideas in improving UX include templates, UIs for choosing amongst generations, the ability to add more constraints, controls over context length, intermediate controls in chained processes, and exposing the “thought process” of models.
Some entrepreneurs and investors have despaired at whether there is business value to be built around someone else’s models, but we are only beginning to understand how to interact with AIs. There is likely to be variability around domain, and researchers are unlikely to address the needs of every user persona. Will the only interface to these powerful models forever be a simple, static text box? I think not – and therein lies a product opportunity.
Trend: Automated code generation and app development
Ultimately, Copilot provides convincing proof that current ML capabilities can automate an increasing amount of code generation and application development. Newly-created startups and well-established companies have started addressing multiple parts of the product-building experience, including automated code reviews, code quality improvements, shell command autocomplete, documentation, and even frontend and website generation.
Trend: Come for the workflows, stay for the personalization
In the next generation of AI startups, the best products will be created by founders who focus on workflow design and fine-tuning models based on user feedback.
Two categories of startups that fit the mold are AI agents and AI-augmented SaaS. AI agents will accomplish repetitive knowledge work — whether that’s being a lawyer, engineer, accountant, or doctor. AI-augmented SaaS will depend on an AI layer to get more value from existing workflows — for example, adding transcription and summarization to a platform that already collects audio data or adding a language interface to streamline SaaS apps. In both cases, a human will still supervise to guarantee output quality. The user will give positive and negative feedback, which will be captured and used to tune the model.
The founders who win will design interfaces and workflows that give users high levels of control and low cognitive overhead by innovating on top of the current prompting and auto-complete modalities. These workflows will accelerate common use cases with templates or specialized composable models while ensuring “break-glass” options are available for uncommon edge cases. The user won’t have to understand how the model works or shape themselves to it. And as the user interacts with the product, the data generated by accepted answers automatically feeds back into the data flywheel that drives personalization and retention.
Startups will leverage the latest advances in AI research by swapping in new models as they become available and fine-tuning based on historical proprietary user feedback. The limitation today is product designers focused on interfaces that make it easy for the non-AI-aware consumer to engage and quickly get value from the models. Moats will be in the comprehensive workflows and data collected as users engage with these models, which will inform more powerful future models.