Hey, it's Bernie!

Maybe this is what a sprint feels like – you give your everything, days, nights and free time all towards one specific goal – jab, jab, jab. You run your best 100m, but ... you didn't get first. Didn't get picked. You were not enough.

That's how I'm feeling right now. Rejection sucks, it unleashes a giant cloud of “what went wrong?”, “I thought it was good”, “What did I miss?”, “Am I really that bad?”, “Was I too full of myself?” thoughts that impairs visions on day 1, but it eventually subsides as a the days go by.

It's been three days since I got rejected from AI Singapore for their Apprenticeship Programme. When I attended the briefing about two months back it felt like something achievable – they were looking to build AI talent in Singapore and you didn't need to be of computer science background nor of any particular age to get selected. I really thought that it was a way for me to build my portfolio and credibility in this competitive sector, and have always had a dream of helping Singapore build her AI competency in a global landscape. I was suddenly brought back to my twenties, when after graduating NUS with a degree in Real Estate, I dreamt about helping shape Singapore's urban landscape by joining the URA. I was rejected then.

Although life presented me with many nice surprises and opportunities after, now 20 plus years later, that “dream unfulfilled” still resides in the back of my mind. I thought that now this time I could try again, this time with AI instead of Real Estate. But maybe life keeps pointing me somewhere better.

Today is Wednesday, April 15, 2026, 11:35am. I'll just grieve over my self-doubt for a few more minutes, then start thinking about different options. I'm deathly focused on committing the next chapter of my life to figuring AI (machine learning, large language models) out, because I believe this is truly the next wave in tech, just like how the age of Internet and digital marketing transformed businesses in the 2000s.

My purpose is not to be housed in a datacentre (like I envisioned), but to get out there to help businesses understand this new transformation. This will be my new focus.

Let's continue building.

#Rejection #Apprenticeship #AISingapore #AIAP #CareerPivot

Last night I went for a live viewing of the BTS concert. This morning I woke up thinking

“I want to listen to all the BTS songs out there”.

So I went to Spotify to curate the albums. Then I thought:

“wouldn't it be great if I can download a full list of songs that BTS ever created”.

So I asked Claude to build me an app that could do just that, called “EverySong”. The code is simple, Claude will search the internet for a list of songs based on a particular music artist, and then create a CSV file. The code will create a filterable list where you can search by release date, album name, singer and read a little description about the song. It took me an afternoon. It was nice to switch from machine learning to music. I had fun.

The repo is on GitHub if you'd like to take a look at the tech stack. – https://github.com/berniepng/everysong

The website is here – https://demo.bernie.studio/everysong

What artist would you like to curate?

#bts #claude #petshopboys #music

If you walk into a room called “Bernie's Life”, there would be piles of mess scattered all over, and one of the bigger piles would most surely be “Financial Literacy and Management”, aka, I suck at holding on to money. So I asked Claude to help me with it.

First I uploaded screenshots of just the credit card transactions from 2025. At this point, it is important to note that you shouldn't upload any sensitive personal information to LLMs, so be sure to delete where necessary.

The first task at hand was to examine all my spends and tell me the hard truths. Turns out a large percentage of my overall spends went to shopping (queue the PSB song ...) and a chunk went to subscriptions. He kept asking me “are you sure you are watching Netflix?” lol.

He started drawing bar charts, pie charts, time series charts. Ok you get the picture. Now I understand where my drifts and creeps are.

I also asked him to set up a folder structure on Obsidian for me, which I found it very useful. I created folders like “Tax”, “Debt”, “Tracking”, etc which will give me a great starting point to document and track all my expenses and revenue.

If you are interested in the prompt I used, I'll share it here. Have you done something similar? Let me know.

"You are a seasoned personal financial planner and life coach. Please advise me on how I should start doing better financial planning for:

1. tax reporting
2. budgeting 
3. gig Scheduling, comparing the hourly rates and making wise decisions and commitments based on goals rather than monetary gains
4. analyse credit card spends to identify areas for optimisation and control
5. establish a savings and investment plan to grow money
6. debt management

Guide me through creating  a plan that form a foundation for the next 10 years.

I'm living in Singapore, so everything should be relevant to the country. 

Get the tax information from
https://www.iras.gov.sg/taxes/individual-income-tax/self-employed-and-partnerships"

#AI #Claude #PersonalFinance

I'm not a historian. I didn't come to this through academic study or political theory. I came to it through a TV show — The Man in the High Castle on Amazon Prime, which imagines an America where the Axis powers won World War II. It unsettled me enough to start asking real questions. What actually happened in Nazi Germany? What programmes existed? How did ordinary people allow it? And — the question I couldn't shake — are we, right now, closer to that world than we think? What followed was a long, uncomfortable rabbit hole through history, AI, power, and human nature. This is what I found.

“Every atrocity in history followed the same first step — making human dignity conditional. We cannot afford to repeat that in the age of AI.”

From the Aktion T4 programme that murdered 300,000 disabled people under medical authority, to today's algorithmic systems denying welfare and housing to the most vulnerable — the pattern is unchanged. Power concentrates. Accountability diffuses. And the people with least voice bear the greatest cost.

The AI revolution is not a new story. It is the oldest story, running on faster infrastructure. Manufactured trust replacing genuine care. Bureaucratic distance laundering moral responsibility. The access gap widening between those who shape these systems and those shaped by them.

But moral progress is real — slavery abolished, democratic accountability expanded, women's rights advanced — not through perfect systems, but through people who refused to accept the current dispensation as permanent.

---

The foundation isn't a new law or a smarter algorithm. It is something every tradition across every century has independently arrived at: human dignity is unconditional, irreducible, and non-negotiable. Not earned. Not conditional on productivity, race, or utility. Simply held — by every person, without exception.

Applied to AI, this means one thing practically: every system that makes consequential decisions about human lives must be able to see the individual, not just the category. Must be accountable to a human face. Must distribute its benefits toward those with least power, not most.

---

But here is where I have to be honest with myself — and where I think you do too. It is easy to write about the failures of systems, institutions, and leaders. It is much harder to admit that I have also been on the wrong side of this. That distance — between me and another human face — has sometimes made it easier to justify a decision that served my convenience over their dignity. A dismissal I dressed up as efficiency. A boundary I called principle but was really just comfort. We are all capable of this. The moral high ground is not a place any of us permanently occupy. The finger we point outward must, honestly and regularly, turn back toward ourselves.

---

Your part in this

Ask one question of every system that affects you — and every decision you make that affects others: whose dignity does this serve — and whose does it cost? You don't need expertise to ask it. You just need the courage not to stop asking until you get an honest answer. Starting with yourself.

#AI #HumanDignity

It was quick and this was my prompt:

"A memorable repetitive beat that can be danced to that sounds like house music with a rap beat. suitable for studying. Instrumental only."

#Gemini #GoogleAI #Multimodal #AudioAnalysis

I’m discovering that the reason why we can create and do stuff so efficiently is as much the effort of AI as it is human effort.

Without the huge repository of human creation through the centuries (the inventors, the artists, the philosophers), AI wouldn’t have a chance to synthesize our knowledge to help the rest of us (the common folk).

AI just made knowledge and creativity more accessible.

But we still need the human geniuses among us to create and innovate. Our imagination needs to prevail for the future of humanity.

That is our value.

Only then, can we work side by side, and not behind, AI.

On a side note, we should re-think how to protect human creativity. Current copyrights and trademark laws need to be revamped.

What do you think? (I'm asking the humans) :)

#AI #HumanAICollaboration #FutureOfWork #HumanCenteredAI #ArtificialIntelligence #Innovation #DigitalTransformation #HumanTouch #AITrends #BerniePng

March has been crazy. Everyday I'm bombarded by AI news – launching of new LLMs, new Claude features, a better way to do things, combining this to that, datacenters sprouting up here and there – and even for someone who loves change, the velocity of AI changes is honestly hard to keep up.

I'm (still) loving every bit of it, and my brain is on fire. Check in on me in 2 months, I might have a different story to tell. Might be fried by then.

Three key mini inflections took place in my life with AI this month:

• 1st week of March

  • The Deliveroo exit from Singapore. I did a symbolic mini tour around almost all the zones, March 1 – 4. It was nice.
  • My attempt to get hired as an apprentice with AI Singapore. On March 4 they sent out the technical assessment to everyone who applied for the apprenticeship program, giving us 6 days to work on it then submit. Wish me luck.

• 2nd week of March

  • I met up with a few of my ex-colleagues. We talked about the future and our plans. It was nice to catch up with them.

• 3rd week of March

  • With the GTC 2026 and SXSW keynotes combines, I finally understood where we are heading, and really gave me a lot to think about, mainly how what value can I offer in this new world, and what gaps I have.
  • I paid for Claude for a month, but have not explored Cowork or Code in depth. I'm still able to build lots of stuff just using the chat.
  • My class assignment for this module 2 involves Big Data. I ingested 23 million rows from a public dataset and did analysis on it. It was fun.

At some point in the keynote Jensen said that in the future we would not just be paid in money, aka salary, but also, with tokens. I believe him. But what does it mean for us, the common folk? He talked about AI factories and showing off all his highly efficient racks with awesome “tokens/watt” servers, and how everything will be opensource. It's like “here's all the free chocolate and candy you can eat, but you have to pay for the teeth.”

Welcome to the new world.

#AI #LLM #FutureofWork #JensenHuang #OpEx #TechnologyTrends

Instead of 1-1 conversation with our AI's, why don't we get together as team members, friends and family members and allow AI to sit at the table with us while we collaborate?

As part of our team assignment for the module on big data, I was looking at what kind of environment data we can find so that we can practice the use of using BigQuery to experience the full ELT pipeline.

Here's the prompt I used.

"You are an environmental consultant tasked to study how air quality of a country is affected by the activities within in, and you are doing a big data analysis to understand, rank and visualize the top 5 industry polluters. You are also to compare these polluters across different countries and show how, if any, what quantifiable improvements made by each country and their results. Guide me through step by step using Google's Cloud Platform's Big Query to ingest a free dataset through API or other real-time data ingestion, preferably streaming, then use a suitable data warehouse to store the data and then do ELT pipelines, then create some prediction models and generate reports through the transformed data. Your final output should be a modern dashboard that can be presented to the United Nations meeting to share the challenges of balancing advancement vs air quality and how poor business decisions can lead to bad air quality and eventually poor health of the people."

So now, it's day 2 and we are working on creating a workflow of using Docker to run Spark to get Air Quality data through API. I'll keep you updated on what happens.

#AirQuality #DataScience #BigQuery #MachineLearning #EnvironmentalData #GoogleCloud #ClaudeAI #DataAnalysis #Sustainability #TechJourney

I like this course by Nick Saraev, so I'm sharing it with you.