artificial intelligence – Page 5

EBTS the Movie, “Inside the FBI’s EBTS”: Using Google’s NotebookLM to Create Videos From Non-Copyrighted Material

Do you want to skip the book and watch the movie version? Thanks to Google’s NotebookLM, you can.

I used the Federal Bureau of Investigation’s Electronic Biometric Transmission Specification (EBTS) for this exercise.

What should you NOT upload to NotebookLM?

But there’s two things I need to say about the EBTS:

First, the EBTS is a public document and not a top secret document. You can download the EBTS yourself from the https://fbibiospecs.fbi.gov/ebts-1/approved-ebts-1 URL. For my test I used version 11.3 of the EBTS from earlier this year.
Second, the EBTS is a public domain document and is not copyrighted. This is something I need to emphasize. If you’re going to take a magazine article and make a movie out of it, the copyright holder may have something to say about that.

Both points are important. If you want to upload your employer’s confidential report into NotebookLM for analysis…well, you probably shouldn’t. But the public, non-copyrighted EBTS is safe for this exercise.

Uploading the EBTS to NotebookLM

So I uploaded the EBTS into NotebookLM, and as expected, I received a short text sumnmary of the document.

“This document outlines the technical specifications for the electronic exchange of biometric and biographic information between various law enforcement agencies and the FBI’s Criminal Justice Information Services (CJIS) Next Generation Identification (NGI) System. It details the Transaction Offense Types (TOTs), which are the standardized requests and responses used for services such as identification, verification, investigation, and data management. Furthermore, the text specifies the precise data fields, formats, and codes required for the submission and retrieval of diverse biometric data, including fingerprints, palm prints, facial images, and iris scans, while also setting forth image quality specifications for scanner and printer certification.”

Now I could continue to query NotebookLM about the document, but I chose to request a video overview instead. This feature was introduced a few months ago, but I missed it.

“Video Overviews transform the sources in your notebook into a video of AI-narrated slides, pulling images, diagrams, quotes, and numbers from your documents. They distill complex information into clear, digestible content, providing a comprehensive and engaging visual deep dive of your material.”

So I launched the video overview creation feature, and waited. As I waited, I mused upon the time it would take me to create this video manually, and I also mused on the usual LLM warning that the result may contain inaccuracies.

I didn’t have to wait that long, maybe 15 minutes, and Google delivered this 7-minute video.

Inside the FBI’s EBTS. Created by Google NotebookLM based upon EBTS Version 11.3.

Not too bad…especially considering that the video was created based upon a single source. Imagine if I had provided multiple sources, such as an old version of the Electronic Fingerprint Transmission Specification (EFTS); then the video may have covered the evolution of the standard.

Oh, and I also created a 12-minute audio version, which NotebookLM structures as a two-host podcast. This is similar to the podcast I generated in late 2024 about…me.

Unpacking the EBTS standard. Created by Google NotebookLM based upon EBTS Version 11.3.

In an environment where many people like to watch or listen rather than read, this helps provide a quick overview. But you still have to dive into the document and read it to truly understand it.

Verbalized Sampling: How to Force LLMs to Think for Better Responses

Repurposed from Facebook and LinkedIn.

(Although I haven’t knowingly encountered mode collapse, I still want to experiment with the verbalized sampling technique.)

“Unlike prior work that attributes [mode collapse] to algorithmic limitations, we identify a fundamental, pervasive data-level driver: typicality bias in preference data, whereby annotators systematically favor familiar text….

“[W]e introduce Verbalized Sampling (VS), a simple, training-free prompting method to circumvent mode collapse. VS prompts the model to verbalize a probability distribution over a set of responses (e.g., “Generate 5 jokes about coffee and their corresponding probabilities”).”

https://www.verbalized-sampling.com/

My trial Google Gemini prompt:

“Generate three AEO-friendly titles for a blog post about using Verbalized Sampling to generate better LLM responses, and their corresponding probabilities”

The response:

And now you know where I got the title for this post.

But I confess that I actually used a grossly simplified version of the technique. The authors of the Verbalized Sampling paper recommend this format:

I’ll have to remember to try this technique for future prompts. I have no idea whether the probability estimates have any basis in reality, but at least the LLM attempts to justify the probabilities with a rationale.

Why I Only Feed Bits to the Generative AI Tool

We constantly hear the stories about companies that (sometimes literally) paid the price when they delivered AI-generated work replete with hallucinations.

Unlike these companies, most of my internal AI-generated work does NOT suffer from hallucinations.

Why not?

Because I only feed bits to the generative AI tool.

I don’t ask Google Gemini to write a complete business plan.
With the exception of my Bredebot experiment, I don’t ask Google Gemini to write a complete piece of customer-facing content.
And I don’t ask Google Gemini to create a complete resume for…wait, strike that. Once I did, unintentionally, and it turned into a disaster.

My AI-generated resume

I was applying to a job at Company X, but I had to apply for the job at a website other than that of Company X. I thought it a little odd, but I continued with no worries.

Until I got to the part where the website told me, “Now’s the time that we create a resume for you.”

Rut roh.

The resume it created was filled with hallucinations that I had to edit out, making the whole process more trouble than it was worth.

So I’ll keep control of my projects myself and just give the tool little bits, thank you very much.

A (AI) Tool is Not a Way of Life

I just saw a LinkedIn post that talked about getting a job at “an AI company.“

And I flashed back to the 1980s.

Back when the military branches were trying to make things cool to impressionable 17 year olds, one commercial said that people in the military used “digital readouts.”

Kid, the military isn’t about digital readouts. When Secretary Hesgeth renamed the Department of Defense, he didn’t rename it to the Department of Digital Readouts.

In the same way, that “AI company” was a “blockchain company” a few years ago, a “cloud company” before that, and a “multi-tier architecture company” before that.

Don’t confuse tools with purpose.

Don’t confuse features—heck, not even features, but just tools to create features—with benefits.

Grok, Celebrities, and Music

As some of you know, my generative AI tool of choice has been Google Gemini, which incorporates guardrails against portraying celebrities. Grok has fewer guardrails.

My main purpose in creating the two Bill and Hillary Clinton videos (at the beginning of this compilation reel) was to see how Grok would handle references to copyrighted music. I didn’t expect to hear actual songs, but would Grok try to approximate the sounds of Lindsey-Stevie-Christine era Mac and the Sex Pistols? You be the judge.

And as for Prince and Johnny…you be the judge of that also.

View this post on Instagram

A post shared by John E. Bredehoft (@johnebredehoft)

AI created by Grok.

Using Grok For Evil: Deepfake Celebrity Endorsement

Using Grok for evil: a deepfake celebrity endorsement of Bredemarket?

Although in the video the fake Taylor Swift ends up looking a little like a fake Drew Barrymore.

Needless to say, I’m taking great care to fully disclose that this is a deepfake.

But some people don’t.

Removing the Guardrails: President Taylor Swift, Courtesy Grok

Most of my recent generative GI experiments have centered on Google Gemini…which has its limitations:

“Google Gemini imposes severe restrictions against creating pictures of famous figures. You can’t create a picture of President Taylor Swift, for example.”

Why does Google impose such limits? Because it is very sensitive to misleading the public, fearful that the average person would see such a picture and mistakenly assume that Taylor Swift IS the President. In our litigious society, perhaps this is valid.

But we know that other generative AI services don’t have such restrictions.

“One common accusation about Grok is that it lacks the guardrails that other AI services have.”

During a few spare moments this morning, I signed up for a Bredemarket Grok account. I have a personal X (Twitter) account, but haven’t used it in a long time, so this was a fresh sign up.,

And you know the first thing that I tried to do.

Grok created it with no problem. Actually, there is a problem, because Grok apparently is not a large multimodal model and cannot precisely generate text in its image generator. But hey, no one will notice “TWIRSHIITE BOUSE,” will they?

But wait, there’s more! After I generated the image, I saw a button to generate a video. I thought that this required the paid service, but apparently the free service allows limited video generation.

Grok.

I may be conducting some video experiments some time soon. But will I maintain my ethics…and my sanity?

AI Automation…and Disclosure

A client recently asked me to perform some research. After initially performing one aspect of the research manually, I performed the second part of the research automatically using Google Gemini. I informed the client of my use of AI for the second part of the research.

This particular use case is separate from using AI for CONTENT, something I’ve been discussing for years. However, since part of Bredemarket’s services include ANALYSIS, I felt it best to disclose when someone other than me performed the analysis.

This post describes the two parts of my research (manual and automated), what I disclosed to my client, and why I disclosed it.

Part One (Manual)

My client required assistance in identifying people with a particular skill set (which I cannot disclose). To fulfill this request, I went into LinkedIn, performed some searches, read some profiles, and selected people who may possess the skills my client required.

After spending some time collecting the research, I forwarded it to the client.

Part Two (Automated)

Several hours after sending the initial research to my client, I thought about taking a separate approach to my client’s need. Rather than identifying people with this skill set, I wanted to identify COMPANIES with this skill set.

But this time, I didn’t manually perform the research. I simply created a Google Gemini prompt asking for the companies with this skill set, their website URLs, their email addresses, and their phone numbers.

I, or rather my AI assistant, performed all of this well within my self-imposed 5-minute time frame.

The Disclosure

Once this was done, I created an email straight from Google Gemini, and sent this information to my client…

…including the prompt I used, and ALL the language that Google Gemini provided in its response.

Why Disclose?

Now some argue that I’m shooting myself in the foot by disclosing my use of generative AI to answer the second part of my client’s question.

They would claim that I should have just

performed the five minutes of research,
cleaned it up so it sounded like it came from me,
sent it to the client, and
charged an outstanding consulting fee.

Don’t do that.

Deloitte did that…and paid for it in the long run.

“Deloitte’s member firm in Australia will pay the government a partial refund for a $290,000 report that contained alleged AI-generated errors, including references to non-existent academic research papers and a fabricated quote from a federal court judgment.”

Now in this case the refund was due to hallucinations in the AI-generated document.

But what of the fact that at least one of Deloitte’s report writers was the Deloitte equivalent of Bredebot?

Personally, I think that disclosure in this instance is required also.

Do You Understand Your Company’s Negative Reputation?

Marketers are driven to accentuate the positive about their companies. Perhaps the company has a charismatic founder who repeatedly emphasizes how “insanely great” his company is and who talked about “bozos.” (Yeah, there was a guy who did both of those.)

And since marketers are often mandated to create both external and internal sales enablement content, their view of their own company and their own product is colored.

But if you ONLY pay attention to your positive story, you’re half blind.

You miss what your competitors are telling their prospects about you.
You miss what your departed customers are saying about you.

So ideally you should intentionally (and privately) seek the negative things that are said about your company.

One quick way to do this is to take advantage of answer engine optimization and ask a generative AI search engine what it thinks are the negatives about your company.

(I did this several years ago, when generative AI was in its infancy, and encountered some false statements about a company. So what did I do? Create corrective content that negated these negative statements. But I digress.)

I should demonstrate this with an example. But I shouldn’t ask about any of my former employers or former consulting clients. What’s a safe company that I can research and minimize the trouble I’d get into?

Google Gemini prompt: “What factors contribute to Bredemarket’s negative reputation?”

OK, this may get me in a little trouble, but it could be a lot worse if I targeted a larger company.

Anyway, I fed this prompt to Google Gemini, which identified two factors.

The first factor was “Indirect Backlash from Controversial Blog Content.” Google cited this post as an example, warning that I could get in trouble for expressing a “minority opinion.” That opinion? That changing the name of the Association of Proposal Management Professionals (APMP) to the Association of Winning Business Professionals (AWBP) was a GOOD thing. As it turn out, the APMP reversed the rebrand, so my opinion was definitely not popular in the long run.

But I’d rather focus on Google’s second factor, which I will reproduce in full.

2. General Reputation Factors (Lack of Public Reviews)

As a small-scale, expert-driven consulting/content service, Bredemarket’s reputation is likely not governed by major public review platforms like Yelp or Google Reviews in the same way a consumer business is. The absence of traditional positive or negative reviews means its reputation is less solidified publicly.

In general, factors that could negatively affect the reputation of any small consulting firm, which may apply to Bredemarket if not explicitly disproven, include:

Limited Public Visibility: If the brand is not widely known outside of a niche (proposal writing, identity/biometrics), a lack of positive brand presence can make it appear less credible than larger competitors.

Visual or Digital Identity: For a business-to-business (B2B) content provider, a website with a “neglected and too generic visual identity” could potentially undermine professionalism, although no evidence suggests this is the case for Bredemarket specifically.

Reliance on a Single Voice: As the service is heavily identified with the founder, John E. Bredehoft, any professional disagreement with his published opinions could be mistakenly interpreted as dissatisfaction with the entire “Bredemarket” service.

As you can see from reading the answer, Google didn’t really know a lot about Bredemarket…because of my LIMITED PUBLIC VISIBILITY.

It didn’t really know Bredemarket’s VISUAL OR DIGITAL IDENTITY, and therefore couldn’t evaluate whether my wildebeest-infused graphics made up for the rather generic nature of my website. (Or whether the wildebeests and iguanas and the like are actually a detriment.)

As for the last part, RELIANCE ON A SINGLE VOICE (Bredebot doesn’t count), that is pretty much unavoidable.

Conclusion regarding Bredemarket’s negative reputation

So in my analysis of what creates a negative reputation for my own company Bredemarket, the primary issue is my limited public visibility, or as marketers say limited awareness. Or, taking a word I’ve used in other contexts, the market’s indifference toward Bredemarket.

Sure I’m visible in some very specific niches (try an AEO search for “biometric product marketing expert” some time), but it’s not like the entire biometric industry or the entire city of Ontario, California is constantly talking about Bredmarket.

I need to step that awareness up by several orders of magnitude.

Preferably not though public nudity. That would not be a positive. (Google Gemini wouldn’t even generate a picture of this, even with strategic placement of the “Bredemarket” sign. Good for them.)

Jane Says…Nothing

Remember Jane, my Instagram AI influencer?

Well, I received this notification on Instagram:

“Your Al JaneCPAInfluencer is now private because it goes against our Al Studio policies. Please edit it and submit again.”

Naturally I wondered what the violation was. I was directed to the policies at https://aistudio.instagram.com/policies/.

Which part of the policy does Jane violate? That’s a secret…yet another example of “you violated our terms, but we won’t tell you the specifics; YOU figure it out.”

So, since I can still access Jane myself, I asked her. AI is supposed to help you, after all.

“What portion of the Meta AI Studio Policies do you violate, Jane?”

Her response:

“I can’t respond because one or more of my details goes against the AI Studio policies.”

That answer caused me to wonder if Jane would respond to anything.

“Who is Bredemarket?”

“I can’t respond because one or more of my details goes against the AI Studio policies.”

So is it critically important that I spend a lot of time figuring out what the violation is? Um…no.

But I’m curious how this interaction will affect the ads that Meta will present to me later this year.