#12: AI With Me by Richmond Alake - Launching into 2023's Latter Half
Launching into 2023's Latter Half
Momentum is underrated, just behind consistency.
The first half of 2023 was noisy, right?
From the reverberations of ChatGPT in every corporate address to Generative AI becoming the buzzword of the current AI hype cycle.
In the midst of this clamour, it quickly became apparent that many generative AI applications were merely flashy demos lacking tangible business value. I, too, built a flashy demo, but I've come to understand the need to shift from the glitz of Generative AI to the practicality of Operative AI, which is all about making AI functional at scale.
However, I encourage you to leverage the hype in a constructive manner. Conduct research, create something, and share your insights with the community. I did this during my talk at the Black Valley event, where I discussed Generative AI and several startups I'm involved with(scroll down for more on this).
Talk is cheap. Action is priceless.
Amid the current noise, there are genuine efforts to build the infrastructure for today's intelligent products. Earlier this year, I delved into Feast, an open-source feature store that facilitates efficient feature management. In a nutshell, features make generative AI work.
Taking my newfound knowledge to the next step, I was able to deliver a live 3-hour training session on the O'Reilly platform.
MiniPT
We recently began internal testing of the MiniPT beta app, a project I co-founded and developed to virtualize the personal trainer experience. Two key lessons from our testing:
- Building in isolation and testing just before release is suboptimal, especially when working remotely.
- Solving a problem you personally experience can lead to quicker product-market fit.
NOTE: We are currently looking for a freelance iOS UI Designer, feel free to connect with me on LinkedIn if interested.
OpenSpeech
Over at OpenSpeech, we've started to invite the first users of our tool built to streamline the generation of the written content creation process from audio data.
Our first users are ideally early adopters; they are individuals willing to provide direct feedback and also handle a tool that contains a few bugs.
How did I find the early adopters?
I'm part of a community of content creators within the AI/ML space
How did I onboard them?
Sent them a video of my uploading one of their youtube videos onto OpenSpeech and generating several high-quality written content in minutes.
How am I following up?
Booking meetings a week after initial onboarding to collect feedback. I'm mainly looking for features that provided value to the user and what they think is missing. The general question I keep as a guiding beacon is, "What will make you pay for this tool now?"
Thanks for reading
Thanks for reading.
Engineer | Builder | Writer | Podcaster
Richmond Alake
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