I created a few Quantum Computing Circuits last night and damn, this is interesting but I still don't know what to do with this.

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Qiskit is the open-source toolkit for useful quantum

IBM Quantum

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Software Developer

Has anyone used Quantum Computing here?- Grapevine

Created a Quantum Circuit that implements Bernstein Vazirani algorithm to find a secret binary substring faster than a classical computer. 

Essentially, if there is a secret substring S then it will take |S| tries for a classical computer to guess it. 
But using Bernstein Vazirani Algorithm does it in a single try.

So, for a secret substring 1001, on a 4 qubit quantum computer, we can do a single shot computation and arrive at the string which was not seen by the circuit. 

Bernstein Vazirani algorithm gets the secret substring exactly as 1001 in ~636 out of every 1000 times. The erroneous values in the histogram for other possible combinations, our original secret substring was 1001, but we can also see that 0000, 0001 …. 1111 were also computed in a few cases, this error seen in the histogram is due to the quantum computing error.

Need Threads on Grapevine: Here's what I did with Quantum Computing

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Quantum computing can vastly improve encryption, process large data, do insane of calculations in considerably less time. What areas do you think we’ll be seeing startup’s built in next 10 years in this domain?

What are your thoughts about quantum computing?

Software Engineer

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Perplexity raises $73.6M from the likes of some big names like Jeff Bezos, Naval, Balaji, NVIDIA. 
Just last month Mistral raised more than $400M in its second funding. AI based startups are the future I guess?

https://twitter.com/AravSrinivas/status/1742918329797574709?t=MtMOF8D3AX6GodNE13pNBw&s=19

Perplexity raises $73.6M at $520M valuation

Site Reliability

I decided to look into some old projects of mine and came up with some interpolation techniques I was exploring for a geo-spatial experiment I was doing early on in my career.

So, essentially I was exploring how do I map out the AQI data collected from various points in Delhi. I wanted to interpolate data between the collected locations. So, I used an approach which used Kriging and allowed me to calculate points in between.

X and Y axis are geo-loc coordinates scaled down by MinMaxScaling.
Z axis(height) is the value collected at that point scaled for plotting.

As you can see, the blue points are the data we collected and green points were the interpolated points.

When we compared this to Weather.com data, we realized that we were within 2-3% of the measured values, which was actually insane.

The inspiration was that, I was scrolling Grapevine and saw someone use Quantum Computers to implement some algorithm. Kinda inspired me to share this hahaha.

Checkout what I did during my undergrad(~7 years ago)

Product Marketing Manager

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What would you do differently in your life?

Comment below!

If you had enough money in your life so that you don't have to work for money, would you still do the same job you are doing?

Consultant

Taking lead from @salt, extending the applications of Monte-Carlo(MC) to silicon circuits simulations. 

I am trying to pick stuff from BTech, 1st year Basic Electronics which most engineers (irrespective of branch) would have studied (or at least heard in class 🤪). Below we have a picture of a very basic Resistor-Capacitor (RC) circuit connected to a battery (Voltage). For theoretical simplifications, we assumed the resistor to have a single, whole-number value (for example, a 5-ohm resistance). In real when we manufacture such resistance (or capacitors), due to complexities associated with manufacturing processes, exhibit a tolerance range around the base value. The resistor we took might exhibit a value between 4.95 ohm to 5.05 ohm. Such range variations lead to changes in currents flowing through these circuits. 

Now imagine, a simple home device having millions of such resistors. All these devices would exhibit different resistance values (some might show 4.95, others might show 5.025, rest 5.05). All these variations make the life of an electronics designer much more complicated. They use Monte-Carlo simulations to explore the range of output current variations and define downstream parameters accordingly. MC makes life bit deterministic in an otherwise uncertain electronics world! 

I hope, I am able to add some value to “geeking-out” series. Shoot your queries, if any🤓

(Image - spice simulation tutorial from Google)

Daily Series #3: Geeking out → Monte Carlo Simulations

Product Manager

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That's not what am saying or pre assuming.

But the brain behind those supercomputers h100 and all, who is making LLMs train faster.

GPT 5.0 can do miracles and imagine 8.0 coupled with those 1nm GPUs.

I still believe that not 100% can be replaced but yes 60-70% roles will be redundant.

Top 10% will survive and thrive if ride the ai wave.

What do u think viners?

But this isn't the first time a tech exec has predicted the death of coding.

Jensen Huang says kids shouldn't learn to code — they should leave it up to AI

Coding will be dead soon

Senior Consultant

I will continue with this series for people who like this kind of content, drop "+1" in the chat and I will tag you the next time I post content.

Imagine you have a very complex situation with varying degrees of randomness. How do you evaluate the probability of certain outcomes? 

One way is a deterministic way which is to sit down and try to compute probabilities of events.
Another way is to simulate these interactions with various seed values and see how these outcomes vary. This is called a Monte Carlo simulation, where we use random sampling to model and analyze complex systems that involve uncertainty.

Let's set up a game and apply a Monte Carlo simulation to it.

You(Hero) and Me(Villain) engage in a strategic coin flipping competition over a series of rounds. Before each round, both of us independently decide whether to flip a coin or pass the turn to the opponent. 

The outcomes are as follows:

1. If both players decide to flip, a fair coin is tossed, and the player who called it correctly gains a point.
2. If one player decides to flip and the other passes, the flipping player gains a point without the need for a coin toss.
3. If both players pass, no points are gained or lost.

We can simulate it by making each decision random:
1. Hero and Villain both independently choose between 0 and 1 for deciding whether to toss or pass. We use 0 as Pass and 1 as Toss.
2. If both pass then we let the scores as is.
3. If one passes and not the other, then we add +1 to whoever decided to toss.
4. If both decide to toss then, we do a random coin flip where 0 = Heads and 1 = Tails. Hero can randomly choose between Heads or Tails. The Villain takes the opposite position.

First is the Monte Carlo Simulation and the difference between potential outcomes for 1000 rounds and 20 simulations, which is the graph shared.

Daily Series #2: Geeking out → Monte Carlo Simulations

Anything happening in AI today can be traced back to this one brief moment in history...

Share your favourite papers. 

GPT ftw :)

Attention is all you need

The Research paper that changed the world...

The race to superintelligence is fully on. Bad news for us humans - compute for superintelligence doesn't seem to be a problem.

Jensen Huang and NVIDIA will not follow any laws made by Moore anymore.

NVIDIA murders Moore's Law

Here's how I modelled my data:
1. Got statistics of the entire Pak and Ind squads with their last 5 performances.
2. Got statistics of Last 3 games at Nassau County Stadium.
3. Got betting odds for all of these matches.

Used a very simple XGBoost model to get the implied odds for betting odds and compared it to the actual odds.
Model did well on Test and Validation set using K-Fold Cross Validation.

Compared the predicted odds and actual betting odds, figured there is some positive E(V) here.
So made two bets of 10k each. Made 8k in 1 match.

Unemotional after winning and unemotional even after loss.

Made Rs. 8000 using Machine Learning models in 1 day...

Lawyer

Always wondered what does the work comprise exactly? Does one do maths all day or little coding with maths? Are the high paying jobs really that stressful? If we are looking to switch from SDE to quant roles, what to focus on? 
TIA.

P.S. From the OAs of some high-end quant roles it seems that they really get into the nitry gritty of a language like C++ and focus on lots of maths, and not much DSA. Do correct me if am wrong.

Quant Roles!

So basically it all started out with my curiosity and me being good at maths and solving analytical and logical problems. Even though I like it doesn’t mean I should be used to do it for like everyday to get paid I mean like my brain literally feels like a 8-core CPU who is constantly working and throttling at 50-80% CPU usage to solve and understand problems that are not mine. Also it’s like I am a computing engine with a life of 20-30 years and completely replaceable with other computing engines like me, they can be better or worse than me I m not gonna be the judge for that. So I feel like I don’t think my life’s goal was to become a computing engine for someone else. This is a recent thought of mine, what do you guys think of it ?

My Life After Being A Backend Engineer

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I am working as QA automation engineer for past 9 years. I want to switch career into other high paying technology.pls suggest what should I consider learning.

Switch technology from QA automation

Software Test- QA

Hi there,
I have technical interview round 1 and 2 scheduled next week on same day for position Engineer: Angular/Nodejs.

Experience 1-3+ yrs : Angular 
1+ SQL
1+ git/SCM

I what type of questions I can expect, what will be level of coding questions and, do they also ask design patterns ?

I have 2.5 years of experience in angular.

Please share your experience if you have any idea of Qualcomm technical interview.


#Qualcomm #interview #prep

Qualcomm Interview preparation

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Has anyone used Quantum Computing here?

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