What do you do if you and your loved one want to be together forever? You work on recreating yourselves as robot clones that aren’t subject to these finicky flesh bags we call bodies. This podcast doesn’t focus on the tech end of this story, but it includes some interesting interactions with and overviews of the work. 🤖
I have been curious about what the future will look like as realistic voice technologies continue to improve since they could conceivably be trained on someone’s social media body of work. Can we create digital twins of ourselves with which we can converse? Will we free ourselves from death not through life extension but through self digitization? Will we consider these digital clones to be a version of us, a human analog? 🤔
Src: This Is Love podcast
Pair with the LifeAfter podcast, a sci-fi story based on people being able to interact with deceased loved ones through the social media history they left behind.
Just a quick note, I am not anti-death. I don’t long for a radically increased life span. I worry about what impact “freeing ourselves from mortality” would have on our humanity and life in general.
A great listen on the practical uses of deep learning in industrial settings, and probably not in the way you think. The guest works for a Fortune 200 energy company. 🔋
I mentioned that I don’t think we’re in the midst of a true AI bubble like some have suggested, and this episode provides some examples for why I think that. If a major energy company has found a way to incorporate this technology into rather mundane tasks that won’t grab headlines but are serving them well, then clearly this is going to be used and useful. 🎥
The example that’s lodged in my head as something really useful and unsexy is using computer vision to monitor whether or not people are wearing the proper safety gear. ⛑
Yeah, it may not grab headlines or pay ridiculous salaries, but it’ll be incorporated into the business landscape, which isn’t so bad in the end. 👌
This episode of Software Engineering Daily is a great listen on the topic of digital evolution, or, the process of allowing algorithms to grow and evolve. 🦖
This field leads to a lot of funny results but there is an important lesson to that, and is probably my favorite moment of the show. We humans are really bad at stating what we want in a way that won’t lead to unforeseen outcomes or loopholes. 🤦♂️🤦♀️
Which makes sense, language is both a tool and a virus. And it functions as much through the interpretation of the recipient as the intent of the user. 🛠😷
Src: Software Engineering Daily
Interesting vision of the future of programming, and one that feels very in line with AI. This episode feels like a companion piece to the podcast episode I shared in the last Listen Up post.
Programming will move away from if-then (which ML engineering does) and start to be more about interacting with and interpreting data.
Though provoking discussion of the future of our data as well.
Great episode of the TWIML+AI podcast on the use of AI in niches with significant domain expertise. The go-to example was creating new types of glass, like Gorilla Glass. Fields where AI can find novel solutions or expedite the R&D process while the human experts weigh in on what’s possible or has already been done.
Especially love this quote from the end:
If you really want to go deep, merging domain expertise and AI/ML expertise, if you can merge those effectively, you can have a super powerful tool that’s really differentiated from what anyone else has.
I think this is an extension of the centaur concept. Also feels like the precursor/initial iteration of a potential future where we all have personal AI assistants/friends/extensions.