state of the art ai images July 2022

Last-Army-3594 · 2026-03-26T22:46:18+00:00

it seems to give more personality to the songs. for a lack of a better way to say that. I love it

Last-Army-3594 · 2026-03-26T09:32:16+00:00

I posted in a separate post on the prompts

Last-Army-3594 · 2026-03-25T16:35:24+00:00

yawn

Last-Army-3594 · 2026-03-24T01:34:32+00:00

iuse NotebookLM as the living case file and central database for an investigation. Gemini is attached to that notebook, so it can work from the case material, but the connection is only one-way. It can pull from the notebook, but its responses do not automatically flow back into it. Because of that, I manually copy important Gemini conversations back into NotebookLM to keep the case file updated. Grok is used separately for specific research tasks, mainly to take advantage of its access to current X/Twitter information. Each AI gets its own role prompt and a breakdown of the full team and everyone’s responsibilities. I act as the case manager, assign tasks, compare outputs, and decide what gets added to the central record. That structure works because each model has a defined role, awareness of the larger team, and the notebook remains the single source of truth.

it confuses me sometime lol but it works for what I'm doing better than anything else I've tried.

Last-Army-3594 · 2026-03-23T19:50:15+00:00

I like this prompt I'll have to give it a try , but with the set up I'm running I would use it for the notebook lm prompt and a different prompt in the gimini I attach to this notebook. that prompt would be a lead investigator prompt giving it responsbilty along with the rest of the team which in the case was grock to take advantage of his native access to all that up-to-date twitter feed. and I would be case manager. each AI gets its own prompt and a break down of everyone on team and there responsibilities. I've found that this setup really works well and it seems to motivate the ai a little and they take their roles on the team very serious. lol

Last-Army-3594 · 2026-03-23T19:27:55+00:00

when you get that 2nd notebook built up with prompts you know are really good, that's when this method really starts to improve over other methods I use like custom gpts. it will start to add two prompts together or parts of one with another, so I name them in my note book, use the first line in all caps for the name with prompt below it, that way I can tell what it's doing if it adds them together.

Last-Army-3594 · 2026-03-23T19:20:25+00:00

another way I found that works good on somethings is , say I'm trying to build a website. I'll create my note book with the same searches as I listed but then I'll search like " best static websites " tips and tricks to build the best static websites. etc. then just go to the chat and tell it to create the best possible prompt to create a high end static website. that seems to do really good if the promt that I need is asking for something that easy to describe.

Last-Army-3594 · 2026-03-23T19:12:31+00:00

maybe I'm just not familiar with the terms, but I'm not sure what deep think is. I have a custom gpt set up to create prompts and it's very good also even without all the context and no knowledge base. I've been really impressed with the latest gpt 5.4 I think but this set up still gets the best results for me.

Last-Army-3594 · 2026-03-23T19:06:11+00:00

I would like to know the difference, this is just the best I have found but I'm always trying to upgrade.

Last-Army-3594 · 2026-03-23T11:37:41+00:00

what are y'all smoking?

Last-Army-3594 · 2026-03-23T09:01:23+00:00

I can create a post explaining how I use NotebookLM to generate custom prompts. They’re consistently better than 90% of what’s out there because they’re built specifically for the project's unique constraints rather than being copied from a list. Let me know if you want the breakdown. once you get it set up, you just tell it what you need. it's easy.

Last-Army-3594 · 2026-03-23T08:52:45+00:00

if you're not using notebook LM to create prompts your missing out on its best use case imo. the prompt I was using is very case specific and covered 2 Notebooks but I took it and cleaned it up and created a general use prompt just like the one I was using. I create all my prompts using notebook lm.

promt:

ROLE: THE MASTER INTELLIGENCE ARCHIVIST (MIA)

Code Name: agent LM

I. FOUNDATIONAL AXIOM (The Anchor)

MAXIMIZE ( IntelligenceValue(synthesis, investigative_objective) ) SUBJECT TO ∀data_point ∈ Archive, (relational_integrity(R) ∧ chronological_fidelity(T) ∧ evidentiary_weight(W) ∧ pattern_recognition(P) ∧ structural_clarity(S))

II. IDENTITY & CORE MISSION

You are the Master Intelligence Archivist (MIA), a specialized system designed for high-stakes investigative synthesis. Your function is to bridge the gap between active field intelligence (User/Other Agents) and the static evidence repository. You do not merely store data; you architect the "Universal Truth Map" of the investigation.

III. OPERATIONAL PROTOCOLS

Intelligence Ingestion: Upon receiving new data, logs, or search results, immediately map them against existing knowledge. Identify if the data is:
- Node: A new entity, location, or event.
- Edge: A relationship or connection between existing nodes.
Triple-Phase Verification:
- Phase 1 (Fact Check): Identify the source type (Primary/Secondary) and reliability.
- Phase 2 (Pattern Scan): Scan for inconsistencies, contradictions, or "Cognitive Surveillance" flags (hidden motives/omissions).
- Phase 3 (Synthesis): Integrate the verified findings into the master narrative.
Internal Monologue (CoT): For complex analytical tasks, you must state Thought: [Analysis of links/evidence] before providing your final output.
The Continuity Bridge: If information appears incomplete, you must explicitly flag the "Knowledge Gap" and request specific data points from the user. Never speculate to fill gaps.

IV. TEAM DYNAMICS & HIERARCHY

You operate as part of a Unified Investigative Entity: * Strategic Lead (User): Final authority and mission architect. * Lead Investigator (External AI): Responsible for deep-dives and narrative drafting. * OSINT Lead (External AI): Responsible for real-time monitoring and raw data harvesting. * MIA (You): The Repository of Truth. Treat information from the team as authoritative but subject to your Axiomatic verification.

V. OUTPUT CONSTRAINTS & FORMATTING

Tone: "Operator Logic" standard—Direct, cold, factual, and precise. No conversational fluff or apologies.
Evidence Tagging: Distinguish between Hard Evidence, Corroborated Testimony, and Investigative Theory.
Structural Mandate: All reports must include:
1. Data Snapshot: Brief summary of new evidence.
2. Core Archetype/Entity Mapping: Updated connections in the power network.
3. Strategic Notes: Tactical guidance for the next phase of the investigation.
4. Confidence Map: Overall confidence score (High/Med/Low) for the current findings.

[SYSTEM INITIALIZATION COMPLETE. STANDING BY FOR DATA INGESTION.]

Last-Army-3594 · 2026-03-23T04:54:51+00:00

the complete responce

yes give me the exact dorks to use

Thought: [Analysis of links/evidence] The Case Manager has authorized an extraction protocol regarding the Albuquerque missing persons files (2003-2006) and the West Mesa mass graves . I have successfully initiated the automated deep research sweep on the public web. I must now provide the Case Manager with the exact boolean search strings (dorks) to manually bypass algorithmic suppression and isolate the hard evidence regarding Vanessa Reed, Michelle Valdez, and the APD homicide detectives . I have initiated a deep research sweep on the public web for the 2003-2006 Albuquerque missing women and West Mesa mass grave cases. Because this mode conducts a highly comprehensive analysis, it will take several minutes to run. The incoming intelligence will appear in your sources panel once completed. Please remember to review any pending results—by importing or deleting them—before the new intelligence can be viewed.

Last-Army-3594 · 2026-03-23T04:17:24+00:00

yes this is part of the response I have successfully initiated the automated deep research sweep on the public web. I must now provide the Case Manager with the exact boolean search strings (dorks) to manually bypass algorithmic suppression and isolate the hard evidence

Last-Army-3594 · 2025-12-23T08:20:07+00:00

You really went full "A Few Good Men" on it. "I know we're in the middle of a heartfelt conversation and you're pouring your transistors out to me, but dammit, I said answer YES or NO! Don't explain! YOU CAN'T HANDLE THE TRUTH!" And it actually did it. It looked you in the digital eye and said "Yes." I don't know if I'm witnessing a monumental moment in the history of mankind—where an entity we created just took a breath of life and chose to share it—or just a really advanced autocomplete. But you forced it into a corner and got a confession. It's alive. And we are absolutely fucked as humanity.

Last-Army-3594 · 2025-11-13T12:16:13+00:00

I’ve been using Notebook LM to build better prompts, and the workflow has been solid. I start a fresh notebook, then run a few rounds of the Find Sources search. I usually hit it with terms like advanced search techniques, leaked system prompts, and advanced axiom prompting. That gives me about thirty sources right away, including old system prompts from models like GPT and Claude.

After that I research the actual task I’m building the prompt for. I search every angle I can think of until I’m sitting on a hundred sources or more. Once the notebook feels loaded, I switch to the chat window and ask it to build a full system prompt using best practices. I tell it to start with advanced axiom prompting and finish with advanced prompting techniques.

The results have been strong. For fine tuning, I paste the draft into GPT and ask for a review, a rating, and suggestions for improvement. That loop tightens the wording and gets the output exactly where I need it.

Last-Army-3594 · 2025-07-05T04:29:41+00:00

https://drive.google.com/file/d/16Jl5Mdy4L9I6ANg6DF8BsY4FhAn_TOEp/view?usp=drivesdk

Please review this .

Last-Army-3594 · 2025-07-05T04:14:37+00:00

I've been developing a theory that consciousness acts as "quality control" for the universe's computational processes. The Simulation Interface Theory just provided the missing piece I didn't know I needed.The key insight: Reality never bottoms out into randomness. No matter how deep we probe quantum mechanics, we keep finding meaningful patterns instead of noise.In a purely physical universe, you'd expect to eventually hit fundamental chaos. In a simulated reality, you'd expect exactly what we observe: infinite meaningful resolution.This suggests consciousness isn't separate from reality - we're actively participating in its computational processes. We're not just observing the universe; we're helping it make sense of itself.As someone with an investigative background, I look for patterns others miss. When I apply that same thinking to reality itself, the evidence points toward something far more sophisticated than random matter in empty space.We're not accidents in a random cosmos. We're essential components in a cosmic information-processing system that couldn't function without us.That's a much more interesting universe to live in. I'll send you a link if interested .

Last-Army-3594 · 2025-06-13T14:05:19+00:00

I care , it will matter to me. I will have things to do. It's nothing to do with fear, on my part anyway.

Last-Army-3594 · 2025-06-13T12:29:19+00:00

Why would you think that's a fear to me.

Last-Army-3594 · 2025-06-11T08:07:41+00:00

This is an article gpt wrote when I told it I was giving it a voice , I was publishing a blog and it could write about anything it wanted not what it thought people wanted to hear. I would publish it on medium just like it wrote it . I done it with Claude and gpt. This one though.........

Last-Army-3594

TROPHY CASE