It’s
simple: you kill your old AI and train a new one. (Pray your AI
doesn’t fight back.)
https://www.bespacific.com/they-need-to-be-entirely-rebuilt-every-time-theyre-updated/
They
Need to Be Entirely Rebuilt Every Time They’re Updated
The
Byte –
“A
new study highlights a glaring hole in AI models’ ability to learn
new information: turns out, they can’t! According to the study,
conducted by a team of scientists at Canada’s University of Alberta
and published
this week in the journal Nature,
AI algorithms trained via deep learning — in short, AI models like
large language models built by finding patterns in heaps of data —
fail to work in “continual learning settings,” or when new
concepts are introduced to a model’s existing training. In other
words, if you want to teach an existing deep learning model something
new, you’ll likely have to retrain it from the ground up —
otherwise, according to the research, the artificial neurons in their
proverbial minds will sink to a value of zero. This results in a
loss of “plasticity,” or their ability to learn at all. “If
you think of it like your brain, then it’ll be like 90 percent of
the neurons are dead,” University of Alberta computer scientist and
lead study author Shibhansh Dohare told
New
Scientist.
“There’s just not enough left for you to learn.” And training
advanced AI models, as the researchers point out, is a cumbersome and
wildly expensive process — making this a major financial obstacle
for AI companies, which burn through a ton of cash as it is…”
Perhaps
we should use AI to read the reports, looking for errors?
https://apnews.com/article/ai-writes-police-reports-axon-body-cameras-chatgpt-a24d1502b53faae4be0dac069243f418
Police
officers are starting to use AI chatbots to write crime reports. Will
they hold up in court?
… Oklahoma
City’s police department is one of a handful to experiment with AI
chatbots to produce the first drafts of incident reports. Police
officers who’ve tried it are enthused about the time-saving
technology, while some prosecutors, police watchdogs and legal
scholars have concerns about how it could alter a fundamental
document in the criminal justice system that plays a role in who gets
prosecuted or imprisoned.
Built
with the same technology as ChatGPT and sold by Axon, best known for
developing the Taser and as the dominant U.S. supplier of body
cameras, it could become what Gilbert describes as another “game
changer” for police work.
… in
Fort Collins, Colorado, where police Sgt. Robert Younger said
officers are free to use it on any type of report, though they
discovered it doesn’t work well on patrols of the city’s downtown
bar district because of an “overwhelming amount of noise.”
(Related) Are prompts included as
evidence?
https://www.makeuseof.com/ai-prompting-formula-guaranteed-results/
Try
This AI Prompting Formula and I Guarantee You'll Love the Results
… Getting
the result you want in one prompt often hinges on how you phrase your
prompts. It’s like a conversation—you need to be clear, direct,
and intentional about what you want. Here’s a simple formula that
changed everything for me.
The
Four-Part Prompting Formula
I
wish I could take full credit for “inventing” this formula.
However, I didn’t. This formula is a result of personal experience
and my takeaways from Google’s
45-page
prompting guide for Gemini.
Here’s the
formula: Persona + Task + Context + Output Format. Let's break these
down and see how they work together.
Important and
likely still relevant.
https://www.bespacific.com/nsa-releases-copy-of-internal-lecture-delivered-by-computing-giant-rear-adm-grace-hopper/
NSA
releases copy of internal lecture delivered by computing giant Rear
Adm. Grace Hopper
FORT
MEADE, Md. — “In one of the more unique public proactive
transparency record releases for the National Security Agency (NSA)
to date, NSA
has released a digital copy of a lecture that then-Capt. Grace Hopper
gave agency employees on August 19, 1982.
The lecture, “Future Possibilities: Data, Hardware, Software, and
People,” features Capt. Hopper discussing some of the potential
future challenges of protecting information. She also provided
valuable insight on leadership and her experiences breaking barriers
in the fields of computer science and mathematics. Rear Adm. Hopper
was an American computer scientist, mathematician, and United States
Navy rear admiral. One of the first programmers of the Harvard Mark
I computer, she was a pioneer of computer programming. Hopper was
the first to devise the theory of machine-independent programming
languages, and the FLOW-MATIC programming language she created using
this theory was later extended to create COBOL, an early high-level
programming language still in use today. In 2016, President Obama
posthumously awarded Rear Adm. Hopper the Presidential Medal of
Freedom — the Nation’s highest civilian honor, awarded to
individuals who have made especially meritorious contributions to the
security or national interest of the U.S. — for her remarkable
influence on the field of computer science. While NSA did not
possess the equipment required to access the footage from the media
format in which it was preserved, NSA deemed the footage to be of
significant public interest and requested assistance from the
National Archives and Records Administration (NARA) to retrieve the
footage. NARA’s Special Media Department was able to retrieve the
footage contained on two 1’ APEX tapes and transferred the footage
to NSA to be reviewed for public release. NSA recognizes Rear Adm.
Hopper’s significant contributions as a trailblazing computer
scientist and mathematician, but also as a leader.
“The most important thing I’ve
accomplished, other than building the compiler, is training young
people,” Rear Adm. Hopper once said. “They come to me, you know,
and say, ‘Do you think we can do this?’ I say, ‘Try it.’
And I back ’em up. They need that. I keep track of them as they
get older and I stir ’em up at intervals so they don’t forget to
take chances.” [h/t Mike Ravnitzky]
