Voice UI | May 21 2024, 16:55

“In one interview, Sam Altman mentioned that what impressed him the most about ChatGPT-4o was the ability to turn on the audio mode in the background and intermittently ask it questions.”

My article from seven years ago:

https://hybrismart.com/2017/06/06/rethinking-the-user-interface-of-tomorrow-voice-and-emotion-recognition-as-auxiliary-channels/

A380 landing | May 19 2024, 02:14

We have an international airport nearby, and planes are almost always in the sky (plus, even closer by, a small airfield where small private planes are constantly taking off and landing). And I’ve noticed something interesting several times—a plane virtually hanging in the air. Just driving along, you look up—at some point in the sky, there’s a plane. Look up a few seconds later, and it’s exactly in the same spot!

Yes, it’s almost always flying almost directly towards me, so the angular velocity is not noticeable. But again, there are many planes flying, and I have something to compare it with. Encountered it again today, but I went the extra mile and checked on flightradar to see what this four-engine aircraft was.

I investigated. It was an Airbus A380—the largest airliner in the world. It’s just big, the wings are huge, and with a strong headwind, and specifically the one I saw was decelerating to 155 km/h according to flightradar24 while approaching for landing. But the following B777 also landed at a similar speed, give or take. The difference is, the B777 is significantly smaller than the A380 (30% shorter in fuselage height and nearly 20% in wingspan), and the same visual angular size for A380 appears at a higher altitude, where angular velocity is lower. Meaning, I saw the A380 when it was further away than I am used to seeing Boeings, and therefore its speed seemed very slow.

Perhaps, in addition to this, there might be a headwind. It can really drastically reduce the plane’s speed relative to the ground. Here I’m “out of my depth” and don’t know what pilots do when landing against the wind.

While I was figuring this out, I read that apparently, the A380 engages its thrust reversers (which direct the engine’s thrust forward) quite late, when the speed drops to 80 km/h. Although a fully loaded Airbus A380 weighs 573 tons, its braking system does not rely heavily on reversers. They are not a mandatory element for airliners, and on the A380, they are installed only on the two inner engines.

Although reversers help slow down the A380, their contribution to braking is not as significant as on most airliners, including the Boeing 747, where thrust reversers do significantly reduce the braking distance compared to brakes and spoilers.

It turns out, A380’s main braking effort is performed by huge Honeywell composite brakes on 16 of the 20 main landing gear wheels. The brakes on the A380 are equipped with a car-like anti-lock braking system. The aerodynamic braking, thanks to 16 large spoilers on the wings, which create drag and reduce lift, also plays an important role. Reducing lift improves mechanical braking, increasing pressure on the wheels.

The A380 slows down from cruising speed of 500 knots (926 km/h) to a complete stop within a few minutes thanks to the overall design of the plane. The descent begins at cruising altitude at about 0.85 Mach (1235 km/h). Below 10,000 feet, the speed decreases to 250 knots (463 km/h), and on the approach glide, the plane moves at 180 knots (333 km/h). The A380 crosses the landing threshold at 140 knots (259 km/h) and touches down at 130 knots (240 km/h).

By the way, here’s how beautifully the landing gear of the A380 extends:

Intercepting and Modifying API Requests and Responses without Code Alterations | May 16 2024, 13:40

I published a new article on my hybrismart. Just imagine, you have a website (frontend + backend) and they are exchanging requests, and you want to change a request on the fly — the parameters or even the JSON that is sent or received from the server back to the browser, all without altering the website’s code. Theoretically, the site might not even be yours 🙂 The reasons can vary — perhaps to test a concept before asking developers to implement it properly, to swap the actual response with a template one, to enable debugging through some debug parameter, to simulate an erroneous/invalid API response, or to remove or alternatively set some headers. For all of this, there isn’t a straightforward free solution “out of the box.” I had to create one myself. The article includes analysis and code that can be used.

https://hybrismart.com/2024/05/16/how-to-inject-custom-logic-to-intercept-and-modify-api-requests-and-responses-without-touching-frontend-backend-code/

Tracking and Visualizing Operational Metrics in E-Commerce | May 12 2024, 15:35

Published a new article on Hybrismart.com. It’s about building a monitoring system for e-commerce business metrics. Things like order volume, SLA compliance for business processes, tracking the creation of new database items, etc. Come read it.

https://hybrismart.com/2024/05/12/tracking-and-visualizing-real-time-operational-metrics-in-e-commerce/

Tracking and Visualizing Real-Time Operational Metrics in E-commerce

Exploring Sheet Sage: Converting MP3 to Sheet Music | May 09 2024, 21:47

I played around a bit with converting mp3 music into sheet music. It’s called Sheet Sage. You feed it a YouTube link, and it spits out a PDF with sheet music and a midi file. The result isn’t exactly great, but it’s better than I expected. Here are two videos—one with the original track, the other with how the midi sounds (I changed the default instruments a bit), and the sheet music right here.

original:

how it sounds:

Exploring Facebook’s LLAMA 3 AI: Local Processing with Promising Outcomes | May 05 2024, 19:03

I’m experimenting with LLAMA 3 from Facebook. There’s a modification called llama3-gradient:8b-instruct-1048k-q6_K, which has a context window of 1M tokens (that’s about 2 megabytes). And there’s even more. I feed it the entire book about Elon Musk (highly recommend it, by the way!) and it produces a pretty good summary—and does it quickly, any text from a screenshot is generated in about 40-60 seconds. And yet, it’s still relatively a weaker model (8B), while Facebook has a 70B. But the main feature here is that all this works locally on a laptop. No need to pay for API, it works quite fast, the script is small, fits on one screen.

Still, there are some rough edges—for example, for direct questions about the text (questions to which I definitely know the answers), the system does not always confidently provide answers. When you send significantly less text, it works fine.