AI Tech Update for Educators 9th Mar

Welcome back to the Titch's AI Cafe. I'm Kane, a teacher and a parent who wants AI to give us

back our time. I share practical classroom-tested AI strategies to cut down your workload and prove

your feedback and reduce stress so you can get your evenings back and be more presently a friend of

family. No jargon, just actual steps, grab your mug and let's get going. This week delivered one

of the biggest AI platform updates for the years so far, though it is only March being March the

nice today. The release of Chatchepity 5.4 comes out as a significant upgrade to what came out

previously. So the most interesting feature educators in this new is the new thinking plan. So when

the model tackles complex requests, it can outline its approach before producing the final answer.

I think this is really good. The old show you're thinking type arrangement. In particular,

terms this allows teachers to intervene early, for example, if you ask Chatchepity to design a

lesson sequence or summarize an historical document you set, you can adjust the structure before

it actually completes the response and fine tune it, saving you a bit more time. It doesn't mean

you've got to pay attention while it's doing. You can't just set and forget and then come back

and modify it, but like I said, the opportunity is there, particularly if you're working on

actively as it goes through. Another big improvement of the model is the ability to handle now

extremely long documents. With the context window approaching a million tokens, basically,

it's going to allow you to analyze very large research collections. Things write extended

curriculum documents in total units of work in a single prompt, whereas before I couldn't handle

that amount of characters. And for teachers work regularly with, I guess, lengthy syllabus materials,

you go a lot of content and you want to put things like academic articles, historical sources.

This could hopefully streamline your prep time because you're doing it all in a single prompt

or discussion at one time, which is an interesting thing. I was looking at people, a lot of people

jumped over the cloud for ethical reasons, but they're apparently using up their limits very

quickly in cloud compared to why Chatchepity works and how they calculate things. Interesting point.

The other thing that came out for Chatchepity is there's an L version for Excel, so instead of obviously

moving dropping spreadsheet data into a Chatbot, now you can put the inside Excel itself with

basically a plug-in to interpret the datasets formulas and explain patterns within the spreadsheet.

And I think that's actually really handy. I use Excel a lot to do analysis and often I do put it

in there so I can now do it in Excel, so I'm looking forward to that particular feature.

And this will just speed up my timeline, my process doing that. So once again,

competition between the different platforms is a tense file. And like I said, the ability to

now export or your chats and move to other platforms is really opening up those opportunities.

Anthropic, which is clause-making expanded memory capabilities in cloud,

even for its free use to act so that basically you can have a long-term conversation memory.

And cloud does a bit different because it'll often scan the entire chat each time it's

white people hitting their limits, if you got a very big chat. But this allows the system to remember

preferences and recurring information over time better than what other platforms actually do.

So in this case, good-make your AI assistant, gradually learn the context of your classroom

where you correct them and focus a lot faster and a lot easier than different platforms.

What's another development? GitHub Copilot, which is Copilot, and now includes Grox. If you

didn't know, GitHub is actually owned by Microsoft. But now you can put the Grox coding model

as part of the automatic model selection if you want to use that there. So this development,

I guess, increasingly students in computing classes using these tools now can interact with more

than one AI model within the same tool, giving them choice, therefore, depending on the projects,

which one gives you the best results. And creates opportunities in the classroom,

around discussing a different system, solve the same problem. And that's very relevant in all

systems, even AI. And before finishing up today's update, one unusual story from the research

community provides a reminder that AI adoption always carries risks. Some security researchers recently

demonstrated large-scale prompt injection attacks hidden in web content. Remember I spoke about

before we're using AI tools to actually go out onto the web. The idea of injection attacks is

they can actually inject malicious code actually into your program there through different websites.

So these attacks can manipulate AI tools. So wouldn't you click, say, summarize button or similar

features? The research has found that this data can actually be loaded into. So as always,

treat AI outputs critically. Always your expert opinion. Verivice your sources, just as you

would with any other research. But when you look at this, these incremental changes, like I said,

talking about Claude, people are moving for ethical reasons over to Claude. And that's

absolutely fine. There's lots of different AI platforms out there. And I'll just reiterate,

there's no one best model or best platform simply because there are ways developing new

updates, competition features, compared to the competitors to try and get that natural advantage.

Therefore, why one might be as good now next week and you release my command and it'll leap frog

the one you're thinking of shifting to. Well, like I said, find one you actually prefer,

what one one that actually does the job for you, stick to it, learn it the best that you can.

All the advice I give really is clickable to every single platform when I do my activities

because they, at the core of them, they do essentially do the same thing just in slightly

different ways. So until then, keep up the good work. If you want to come on and talk about your

journey, drop me an email. Till then, look after yourself.