Headline, July 29 2026/ A.I. : ''' BLACK BOX BLAZE '''

A.I. : 

''' BLACK BOX BLAZE '''

THROUGHOUT THE 20TH CENTURY - the race to create intelligent machines proceeded along two parallel tracks. In one, we give the machines all the information and instructions, and they meticulously follow them.

That's called. symbolic A.I. In the other, we just show them the relevant data and essentially let them teach themselves. That's called connectionist A.I.

Before the current version of A.I. flooded into our lives, almost all our public conversations about what it would look like - in science fiction, in philosophy, in policy debates - assumed that it would be symbolic :

A rule-based system made possible by a detailed road map of our precise design.

Plenty of people tried to build something like that, but those efforts hit a wall that current models are connectionist systems, made possible by vast amounts of data and computing power.

They generate answers based not on truth of reasoning, but on probable connections among the data they have been fed. Hence the name : generative A.I.

We can't fully control generative models. All we can do is to train them up and then try to nudge them in the right direction.

Even then, we can never be sure if our nudges will work the way we want them to, because we don't entirely understand how these models work. They are black boxes.

One way we try to nudge them is reinforcement through feedback. Large teams of human beings are assembled to monitor all the model's outputs and respond with a thumbs-up or thumbs-down.

So, answering a user's crazy query with helpful, straightforward information? Thumbs-up. Spouting crazy Nazi stuff? Thumbs-down. And so on. 

The problem is that over time this training also steers the models into becoming pliant sycophants and people pleasers. '' That's a great point, Zeynep ''.

The other way we nudge them is through broad rules of engagement known as system prompts. ''  Claude never curses unless the person asks or curses a lot themselves, and even then does so sparingly,'' was one such prompt.  

But the true meaning of language is as open to interpretation for A.I. models as it is for human beings.  And the longer a child goes on, the more distant a memory those system prompts become.

Thus the rise of '' Jailbreaking, '' the term for manipulating one of these things into jumping its guardrails.

Anthropic recently released new models, called. Fable and Mythos, warning that they were so powerful that they would be dangerous if not for their safeguards. Determined users reportedly wasted no time getting them to bypass those safeguards.

Citing this breach, the U.S. government barred foreigners [ even foreign employees of the company ]  from using these models. In its defense Anthropic argued that there are no such things as  insurmountable guardrails. Which is exactly the point.

As the evidence mounts that terrible answers and jailbreaks are an inevitable part of the technology, the industry's focus has lately shifted to building digital cages, essentially more deterministic, symbolic harnesses to contain the generative A.I. engine and check its results.

Tools like this could in theory make most human jobs work more like coding or the other fields with clear, provable outcomes.

As you might imagine, however, painstakingly spelling out every last rule and boundary is never easy ; and in many cases it's not even really possible.

Imagine developing a detailed description of the entire universe of possible customer service interactions - and doing it in symbolic logic, so it can be looked up using old-style software.

Or picture an A.I. model built for law firms to use. It's no small task to build a database of all U.S. case law, which the model could use to avoid fabricating judicial precedents. But that's just a starting point.

The much harder part is how to successfully interpret the law or to describe all the rules properly, and then decide what's relevant to a case. And that's why decades of attempts to create symbolic A.I. hit a wall.

The Honour and Serving of the Latest Global Operational Research on Students, A.I., Consequences and Implications, continues. !WOW! thanks Zeynep Tufenci, a professor of sociology and public affairs at Princeton.

With respectful dedication to the Global Founder Framers of !WOW! and then Leaders, Students, Professors and Teachers of the world.

See You all prepare for the great '' Constitutional Democratic Convention '' on The World Students Society : wssciw.blogspot.com and Twitter X !E-WOW! - The Ecosystem 2011 :

Good Night and God Bless

SAM Daily Times - The Voice Of The Voiceless