@kerckhove_ts It works, but it doesn't play the same in the new AI world.
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david bennett
1.6K posts
david bennett
@Davidus_Rex
IT guy, founder, investor, thinker, member of Melbourne Angels, worried for the planet
Melbourne Katılım Nisan 2014
105 Takip Edilen61 Takipçiler
I keep hearing that developers write code too early in the whole "getting things done" process but my experience says the exact opposite.
The only real way I've found to figure out requirements IS to start writing code and see what I bump into.
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@pickover You're imaging things. There is no triangle, grasshopper.
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Mathematics and Mystery.
The strangest right triangle you'll ever see. Nicely satisfies the Pythagorean Theorem. Drives humans insane.
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Looks SIMPLE… but 90% get it wrong 😳
Can you predict the output correctly?
Don’t guess — think carefully 🧠
Vote or comment your answer 👇
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@engineers_feed Boring. 27. Can't you find any more interesting puzzles?
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@WorkElizab Looks like a triode-pentode (valve) as used in TV. Never actually seen one of these, but could be an 11MS8 based on this: external-content.duckduckgo.com/iu/?u=https%3A…
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I'll bet you won't recognize this – but if you do, you've clearly got some serious expertise!
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@livingdevops Yes, but he was just a geek who got lucky by being in the right place, picking up all the pieces from those around him. In fertile soil whatever you plant will grow, especially weeds like C.
It's still useful if you really value small size and hardware access, otherwise avoid!
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Dennis Ritchie created C in the early 1970s without Google, Stack Overflow, GitHub, or any AI ( Claude, Cursor, Codex) assistant.
- No VC funding.
- No viral launch.
- No TED talk.
- Just two engineers at Bell Labs. A terminal. And a problem to solve.
He built a language that fit in kilobytes.
50 years later, it runs everything.
Linux kernel. Windows. macOS.
Every iPhone. Every Android.
NASA’s deep space probes.
The International Space Station.
> Python borrowed from it.
> Java borrowed from it.
> JavaScript borrowed from it.
If you have ever written a single line of code in any language, you did it in Dennis Ritchie’s shadow.
He died in 2011.
The same week as Steve Jobs.
Jobs got the front pages.
Ritchie got silence.
This Legend deserves to be celebrated.
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@r0ktech It could be 13, but depending on the language and how x and y are defined, there are multiple other possibilities.
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@Kekius_Sage It means we have data showing objects in space are receding from us in proportion to their distance. Expansion is a theory that fits the data. Just read the science.
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If the universe is expanding, but not into anything, what does expansion really mean?
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learn programming in C.
not because it is trendy.
because it exposes how computers actually work.
in higher-level languages memory, hardware, and execution are hidden behind abstractions.
C removes most of that.
you confront the real machine:
• manual memory management
• pointers and addresses
• stack vs heap
• direct interaction with hardware
• predictable performance
entire systems are built on it:
• the Linux Kernel
• the CPython interpreter
• embedded firmware
• operating systems
• compilers
• device drivers
C teaches the architecture of computing.
memory layout.
data representation.
how instructions interact with hardware.
once this layer is understood, every higher-level language becomes easier to reason about.
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@Kekius_Sage Please learn your science. Velocity is only relative, acceleration requires a force. Your scenario allows for neither.
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Imagine something like a ball drifting through deep space with absolutely nothing around it. Acceleration is the derivative of velocity with respect to time.
So how do you even know the ball is moving, if there’s nothing to compare it to?
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6 for me!! I feel confident nobody
Has all 20
How many for you?
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@alphafox Bollocks. My first was a CP/M micro in 1979, but there were lots of other personal computers around at that time. IBM just made it credible for business users.
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@r0ktech Bad code. In some languages that will crash, in others you have to read the fine print. In Python, who cares? Just don't do it.
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@slow_developer Bollocks. You make claims like that you have to back them up with solid published facts or they're worthless.
My guess is I could drive truck through whatever metric you're using.
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we don't really talk much about the IQ metric
but we've gone from roughly 83 iq to 130 with gpt-5.4, and the next major model update could easily push past 140
ai iq obviously isn't a great way to judge overall model quality, but the raw cognitive ceiling is improving fast
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@arpit_bhayani Yes, but who cares? If a linked list makes your code faster to write, better to read, easier to test then use it and worry about faster only when you really have to.
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Let me talk about something obvious but with a bit of quantification...
Theoretically, both arrays and linked lists take O(n) time to traverse, but here's what actually happens when you benchmark by summing 100k integers
- Array: 68,312 ns
- Linked List: 181,567 ns
Summing an array is ~3x faster than LinkedList. Same algorithm, same complexity, but wildly different performance.
The reason is cache behavior. When you access array[0], the CPU fetches an entire cache line (64 bytes), which includes array[0] through array[15]. The next 15 accesses are essentially free. Arrays hit the cache about 94% of the time.
Linked lists suffer from pointer chasing. Each node is allocated separately by malloc(), scattered randomly in memory. Each access likely requires a new cache line fetch, resulting in a 70% cache miss rate.
This is a good example of why Big O notation tells only part of the story. Spatial locality and cache-friendliness can make a 2-3x difference even when the theoretical complexity is identical.
I am sure you would have known this, but this crude benchmark quantifies just how fast cache-friendly algorithms can be.
Hope this helps.
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@TrueAIHound Too harsh. On a journey of a thousand steps we've covered at least the first ten.
And you need to look up 'AI winter'. This is just the latest iteration, and this too shall pass.
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In over 70 years, the AI community has made zero progress in solving intelligence. Indeed, they are more clueless now than they were when they started.
Why do I say this? It's because the AI community has doggedly insisted on conflating automation with intelligence. Their most powerful automation tool, deep learning, was so successful, they became convinced they were making progress toward solving AGI.
Now they are fully addicted to the DL opiate. There is no treatment. They are stuck in a local optimum of their own making. It's so deep, they can't see the way out.
It's a beautiful thing to observe. I admit that I'm loving it. No community deserves to fail more than the AI community. 😁😀
Pedro Domingos@pmddomingos
OpenAI is the Apollo Program of AI, and so was Cyc.
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@MrEwanMorrison It's a dead end like a road to a beach. You can swim and play and have fun, but you can't get to the other side.
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I've been saying this for a year.
LeCun and Marcus are right.
The current AIs (LLMs) are a dead end.
Spending a trillion on data centres build won't advance them.
It's a futile waste & a cause of environmental & human damage that won't yield results.
Milk Road AI@MilkRoadAI
The man who built Meta’s entire AI research operation just made a $1 billion bet that everything OpenAI and Google are building is a dead end. Yann LeCun helped design the deep learning systems that made today’s chatbots possible. He spent years inside Big Tech, then walked away and called current AI “very stupid.” Because he says it only plays with words. LeCun says today’s models don’t truly understand the physical world, don’t keep real long‑term memory, and can’t genuinely reason or plan. They just predict the next token and sound smart while doing it. So he left to build something completely different. His new startup, AMI Labs, is trying to build world models, an AI that learns how reality itself works. Not just text in, text out but systems that watch video, interact with environments, and build an internal map of cause and effect. LeCun believes that once these systems can predict the future and care about consequences, they’ll even show emotion like states such as fear, excitement, anticipation. That’s why the stakes are so high. If he’s wrong, the LLM giants keep scaling and win by brute force. If he’s right, today’s AI leaders are racing down a side road, while the real path to machine intelligence is being built somewhere else.
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@engineers_feed Boring. 2 min to clear the tunnel.
And please: the world is metric, engineering is metric, please adapt.
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World of Engineering Quiz:
A 300 ft. train is traveling 300 ft. per minute must travel through a 300 ft. long tunnel. How long will it take the train to travel through the tunnel?
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