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Why did #Anthropic decide not to release #Mythos, its most powerful #AI model yet? #cybersecurity
Why did #Anthropic decide not to release #Mythos, its most powerful #AI model yet? #cybersecurity
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उपशीर्षक (55)
0:00
Anthropic just pulled off one of the
0:02
most unusual moves in AI history. The
0:04
company built what may be its most
0:06
powerful AI model ever called Mythos and
0:08
then chose not to release it. So what's
0:10
really going on? There are three main
0:13
explanations. First, the official
0:15
reason. Mythos is extraordinarily
0:17
capable in cyber security. The model
0:19
found thousands of serious software
0:22
vulnerabilities, including flaws in
0:23
major operating systems and browsers
0:26
that humans had missed for years. That
0:28
led Anthropic to launch project
0:30
Glasswing, which gives trusted partners
0:32
access to the model so they can patch
0:34
systems before these capabilities become
0:36
widely available. The AI security
0:39
institute found that OpenAI's GPT 5.5
0:42
model is similarly capable. So this
0:44
undermines the official stance a bit.
0:46
Second, the compute theory. Mythos is a
0:49
huge expensive model to run. Anthropic
0:51
has been dealing with massive demand for
0:53
Claude and has openly talked about
0:55
expanding its compute capacity. Some
0:58
experts have argued that Anthropic
1:00
simply didn't have enough infrastructure
1:01
to launch Mythos at scale. Now, after a
1:04
string of new compute deals, Axios
1:06
reports Anthropic is preparing to
1:09
release Mythos level models more
1:10
broadly. Coincidence? I will let you
1:13
decide. Okay. Third, the competitive
1:16
theory. AI companies increasingly worry
1:18
about something called distillation.
1:20
When a Frontier model is released,
1:22
rivals can collect its outputs and use
1:25
that data to improve their own systems.
1:27
Anthropic may simply want to keep its
1:29
best capabilities out of competitors
1:31
hands for as long as possible,
1:33
especially from open- source rivals and
1:35
fastmoving Chinese AI labs. The bigger
1:38
takeaway is this. For years, the AI race
1:40
was all about releasing bigger and
1:42
better models as fast as possible.
1:44
Mythos suggests the next phase may be
1:47
different. The future may be less about
1:49
who builds the smartest model and more
1:52
about who can deliver these products the
1:54
most efficiently to the biggest
1:56
audience. To read more about anthropic
1:58
mythos and the next phase of the AI
2:01
race, head to Business Insider.