Rob Bowley

Technology Leader | Advisor | Mentor.

No longer active here, find me on Bluesky @robbowley.net or LinkedIn

[Rob Bowley @robbowley]

@GergelyOrosz @Pragmatic_Eng It would be great to see you posting more on BlueSky. See you have an account. A lot of folks have moved over in the last few weeks (UK, Brazil).

You can use https://t.co/m6uAZkV5Ss to make it easier to cross post

[Rob Bowley @robbowley]

I'd you're personally looking for a last straw to leave this platform 👇

[Rameses Niblick III @TheLittleWaster]

The bloke behind this account was jailed for 3 years today. Came out in interview he was making £1400 per month from X.
Yip, he was being paid to post his vile filfh.

[Rob Bowley @robbowley]

Not tried it yet as on hols

https://t.co/PYywofBJ28

[Rob Bowley @robbowley]

Enjoying setting up home on BlueSky. Very much has the feels of early Twitter.

Lots of activity with other people moving over too (esp UK folks)

Have been recommended the Sky Bridge Chrome extension for finding and migrating ppl you follow here (link in reply)

[Luke Tryl @LukeTryl]

🧵What do the public think about the riots and those taking part in them? A reflection of legitimate concerns Or the actions of far right thugs? I've written for @FT today on new @moreincommon_ polling and focus group research into Britain & the riots. https://t.co/103UwZeCn0

[Rob Bowley @robbowley]

First impressions of Bluesky - I like it and feel it's worth the effort of building back up over there.

Most ppl I follow here have accounts there (see my Bsky follows if you're looking for folks)

Let's face it, this place isn't going to get any better....

[Rob Bowley @robbowley]

I've not really been posting on here for a while, used to love this place

Slowly migrating to Bluesky, let me know if you're on there (if you're still here, most seem to have gone already)
https://t.co/EUF1iUzXaH

Also:
https://t.co/d3ws1HHX5a

[Kevin Schawinski @kevinschawinski]

X added a setting for "we'll take your data to train grok" without any notice and just defaulted to "yes" for everyone.

This is BAD.

[Rob Bowley @robbowley]

@MartinDotNet Only "always" if you're experienced enough to make those kind of judgement calls.

Many more teams than you'd like to think are lacking the level of experience needed to do so.

[Timothy B. Lee @binarybits]

People who think agi is imminent aren’t overestimating how quickly ai will improve. They are underestimating how complex the world is. Being an expert on deep learning doesn’t necessarily make you an expert on how the world works.

[Stephen Wolfram @stephen_wolfram]

How do the LLMs compare? Leveraging our "code grading" tech to introduce weekly computationally grounded LLM benchmarking...
https://t.co/dPxB0ppZvA

[Ed Zitron @edzitron]

Newsletter: Goldman Sachs has called BS on Generative AI, and I believe that it's time that everybody follows suit - generative AI is unreliable, unsustainable, requires an entire rebuild of America's power grid, and is most decidedly not the future.
https://t.co/YULEkHYBFP

[Bilgin Ibryam @bibryam]

Java is dead
Kubernetes is dead
DevOps is dead
And now: Serverless is dead...

In this context, 'dead' means: mature, stable, well understood by the industry. It's not the hot topic for marketing, devrel, or conferences anymore.

[Ian Cooper @ICooper]

Given the divergence of platforms, I decided to return to blogging for longer form thoughts.

To start, I thought I might as well offer an opinion on the question of the day: Is AI A Silver Bullet?

https://t.co/HT9P3pXiAQ

You will want a coffee; it's long.

[BURKOV @burkov]

What surprises me about talented people in tech is their capacity to be brilliant in one area and entirely delusional in another, even within their domain. For instance, those who invented modern machine learning, fully aware of its mechanics and inherent weaknesses, might still claim, "Superintelligence is near; we need to prepare." I want to scream, "How can you, knowing exactly how it works, believe it will soon consume us?" Yet, they somehow do.

A language model, however good, is still a machine learning model—a simple mathematical formula whose parameters are only as good as the dataset used to estimate them. Any dataset, no matter how large, has high-density regions, like news articles or fiction books, and low-density regions, like cutting-edge scientific and medical articles. Thus, the model excels in high-density areas and becomes unreliable in low-density ones. Anyone capable of training an LLM knows this; it's common machine learning knowledge. Yet, they persist in saying "superintelligence is near."

So, I wonder if it's just human nature to excel in one area and be utterly mistaken in another, or if they are cold-blooded liars causing panic to profit from scared people?

[Rob Bowley @robbowley]

@GaryMarcus Thanks for replying :)

[Rob Bowley @robbowley]

@GaryMarcus The data improvement opportunities now are quality rather than quantity, which will all be very expensive. Either human created (there are probably $bns being spent on this already) or licensed

[Arvind Narayanan @random_walker]

In the late 1960s top airplane speeds were increasing dramatically. People assumed the trend would continue. Pan Am was pre-booking flights to the moon. But it turned out the trend was about to fall off a cliff.

I think it's the same thing with AI scaling — it's going to run out; the question is when. I think more likely than not, it already has.

[Rob Bowley @robbowley]

@channingwalton It's the hardest thing to do and takes lots of experience.

Also, "smart" engineers (much brighter than me) love to make things complicated, I'd guess because it validates their intelligence.

See any time anyone uses reflective or asynchronous programming