Vidya M Shankar

Industrial Al, MLOps engineering , Industry 4.0 , #AIforGood, #Sustainability, #OrganicLiving, #philanthropy. On my startup journey 💪🏻

[Vidya M Shankar @VidyaMShankar]

Yay, completed MicroMasters in Business Analytics !! https://t.co/secutsz6U4 Thanks @edXOnline and @Columbia . Happily applying the skills now !!

[Vidya M Shankar @VidyaMShankar]

@DarioAmodei @eugeneyan The only way to have AI work safely is to penalise ( legal , monetary ) the wrong behaviour of AI . So anyone who is the rightful owner of AI model or its application is responsible for the penalty .

[Vidya M Shankar @VidyaMShankar]

@hilbertspaess @manlikemishap Do you have any suggestions on how should OpenAI or Anthropic or in fact any company into creating the models (self learning ones) do their work ethically for humanity ? Arriving at AGI is something very innovative but not at the expense of human lives.

[Vidya M Shankar @VidyaMShankar]

@karpathy Just curious to understand then how do you nourish human creativity ? Since code is no longer written by human , creativity lies in the end product ??

[Vidya M Shankar @VidyaMShankar]

@MrinankSharma Very rare to find people who uphold their values !! So thanks, kudos and all the best!

[Vidya M Shankar @VidyaMShankar]

@AndrewYNg AI for sure has improved the work efficiency and productivity as long as the foundational model is performing well . But end of the day we need a human to be “responsible/ liable” for the tasks in an agentic AI world.

[Vidya M Shankar @VidyaMShankar]

@AndrewYNg Hi @AndrewYNg . A little perplexed on the shift of creativity . Earlier there was always a need of a simple , concise and optimised code. Such work was noticed , rewarded and benchmarked. How does that work in this age of coding with AI ?

[Andrew Ng @AndrewYNg]

Writing software, especially prototypes, is becoming cheaper. This will lead to increased demand for people who can decide what to build. AI Product Management has a bright future!

Software is often written by teams that comprise Product Managers (PMs), who decide what to build (such as what features to implement for what users) and Software Developers, who write the code to build the product. Economics shows that when two goods are complements — such as cars (with internal-combustion engines) and gasoline — falling prices in one leads to higher demand for the other. For example, as cars became cheaper, more people bought them, which led to increased demand for gas. Something similar will happen in software. Given a clear specification for what to build, AI is making the building itself much faster and cheaper. This will significantly increase demand for people who can come up with clear specs for valuable things to build.

This is why I’m excited about the future of Product Management, the discipline of developing and managing software products. I’m especially excited about the future of AI Product Management, the discipline of developing and managing AI software products.

Many companies have an Engineer:PM ratio of, say, 6:1. (The ratio varies widely by company and industry, and anywhere from 4:1 to 10:1 is typical.) As coding becomes more efficient, teams will need more product management work (as well as design work) as a fraction of the total workforce. Perhaps engineers will step in to do some of this work, but if it remains the purview of specialized Product Managers, then the demand for these roles will grow.

This change in the composition of software development teams is not yet moving forward at full speed. One major force slowing this shift, particularly in AI Product Management, is that Software Engineers, being technical, are understanding and embracing AI much faster than Product Managers. Even today, most companies have difficulty finding people who know how to develop products and also understand AI, and I expect this shortage to grow.

Further, AI Product Management requires a different set of skills than traditional software Product Management. It requires:
- Technical proficiency in AI. PMs need to understand what products might be technically feasible to build. They also need to understand the lifecycle of AI projects, such as data collection, building, then monitoring, and maintenance of AI models.
- Iterative development. Because AI development is much more iterative than traditional software and requires more course corrections along the way, PMs need be able to manage such a process.
- Data proficiency. AI products often learn from data, and they can be designed to generate richer forms of data than traditional software.
- Skill in managing ambiguity. Because AI’s performance is hard to predict in advance, PMs need to be comfortable with this and have tactics to manage it.
- Ongoing learning. AI technology is advancing rapidly. PMs, like everyone else who aims to make best use of the technology, need to keep up with the latest technology advances, product ideas, and how they fit into users’ lives.

Finally, AI Product Managers will need to know how to ensure that AI is implemented responsibly (for example, when we need to implement guardrails to prevent bad outcomes), and also be skilled at gathering feedback fast to keep projects moving. Increasingly, I also expect strong product managers to be able to build prototypes for themselves.

The demand for good AI Product Managers will be huge. In addition to growing AI Product Management as a discipline, perhaps some engineers will also end up doing more product management work.

The variety of valuable things we can build is nearly unlimited. What a great time to build!

[Original text: https://t.co/OIeAQXpriK ]

[Vidya M Shankar @VidyaMShankar]

@eugeneyan Cool work ! Thanks for sharing !!

[Vidya M Shankar @VidyaMShankar]

@eugeneyan Also , could I please know : 1. How long did you take to design and code the App with the help of AI tools ? An Approximation ? . 2. What would be the cost of using the AI based help such as Claude model , https://t.co/dGVAWcoSBp , cursor ?

[Vidya M Shankar @VidyaMShankar]

@eugeneyan @foxhu007 Any idea on optimising the rendering speed for such use case ?

[Vidya M Shankar @VidyaMShankar]

@eugeneyan *meant development timeline .

[Vidya M Shankar @VidyaMShankar]

@eugeneyan Oh wow ! 30 hours . AI does reduce the development work by a half atleast! And regarding the cost , AI based development may be charged at a premium 🤔 Just thinking about the various businesses that need software development ….

[Vidya M Shankar @VidyaMShankar]

@eugeneyan May suggest feature for the beginners - such such as recommendation [ one feature which invariably exists on all websites] .

[Vidya M Shankar @VidyaMShankar]

@eugeneyan Hi @eugeneyan . This is just what I was looking for . Thanks for the post . I feel other than the avid readers , useful application for teachers/ educators .

[Vidya M Shankar @VidyaMShankar]

@AndrewYNg @upstageai @hunkims @echojuliett Looking forward to the course. Love the way courses are designed in https://t.co/QMT0DD0K5J - so apt, relevant and explorative. Thank you for the platform @AndrewYNg .

[Brett Adcock @adcock_brett]

Spent the last 20 years building software & hardware companies

> Last software company sold for $100M
> Then took my company public at $2.7B

Here are my top 9 lessons learned:

[Vidya M Shankar @VidyaMShankar]

@exceleducations 32

[Vidya M Shankar @VidyaMShankar]

@sama Sahara desert with constant 100 days of rain.

[LandingAI @LandingAI]

Join @DavidDechow next week for a discussion on prominent technologies that are enabling vision-guided #robotics and key applications where VGR is gaining traction.

More info: https://t.co/8ZMpXIePjT via @Vision_Systems #automation

[LandingAI @LandingAI]

It was great to see everyone at #Automation Taipei!

Thank you to our partners D-Edge and VS Tech for hosting us in your booths.

Learn more about D-Edge: https://t.co/ywXT61wjZM
Learn more about VS Tech: https://t.co/SKAmGfm3o9

#DeepLearning #ComputerVision