San Francisco, CA
Joined October 2024
The Courses of Action module of the VectorForge platform is a perfect illustration. xitter.cf/vectorforgeai/status/1…
Replying to @haider1
LLMs have inherent architectural shortcomings that make their use in mission critical applications a rather poor choice. Courses of Action, particularly for Defense applications, need to leverage advanced World State technology. Deep Labs has been pioneering that technology for a decade and is a clear leader in the space.
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The DIVT (Data Integrity Validation Token) technology by @NKrypt_Inc , creates a Military-Grade cryptographic trust chain where every data point is verifiably secured, auditable, and tamper-proof, ensuring integrity from ingestion to final decision. DIVTs, coupled with the Large Signal Model (LSM) technology by @deep_labs enables our solution to be resilient against AI manipulation/poisoning and ensures the same security principles that protect the world’s most classified intelligence are leveraged for High-Stakes environments and mission critical applications. #zerotrust #worldmodels #AI #quantum
Fun Fact: The aggregate information flow in the global RF environment is on the order of exabytes per day. The Earth's RF environment (human generated) constitutes an extraordinarily dense, continuous, and multi-source signal field that no existing LLM can ingest or process in its entirety. Even state-of-the-art models with 1–10 trillion parameters operate under fundamental constraints that make real-time processing of Earth's full signal environment impossible: Consider that the total number of distinct signal instances is effectively in the trillions when measured over short time intervals: - Billions of mobile devices perform frequent handshakes, paging, and data bursts. - IoT deployments now exceed 15–20 billion connected devices, many transmitting periodically. - Satellite constellations blanket the planet with overlapping beams. - Broadcast stations and radar systems operate continuously. The aggregate information flow in the global RF environment is on the order of exabytes per day (or petabits per second in raw sampled data). Sampling the entire usable RF spectrum at Nyquist rates across all locations would generate data volumes far exceeding global internet traffic. But what if there was a way to deal with the unique volume and disparate signal types to truly model the global RF environment? You would need advanced compression capabilities, hierarchical predictability mirroring human perceptual processing, and multi-resolution representation amongst other inherent capabilities. The World State, and its fundamental enabler Large Signal Model (LSM) technology, provides the necessary architecture and capabilities necessary to truly model and thoroughly examine the RF world. @deep_labs has been delivering this technology to meet the demanding needs of mission critical applications across Financial Services, Defense, and Critical Infrastructure. #AI #LargeSignalModel #Worldmodels @WorldState
There's a new version of this post
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Prepping for an upcoming Situational Awareness test of our GHOST capabilities for our defense partners.
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An exciting release for our partners who rely on our World State capability to power advanced decisioning across Cyber, Financial Services, and Defense. deepdecision.ai/news/deep-la… @VectorForgeAI
Our team is very excited to announce the latest advancement in Large Signal Model (LSM) technology! Unlike conventional large language models optimized for text generation, DeepDecision® LSMs are purpose-built to ingest, correlate, and reason over multidimensional signals at scale. The newly released architecture expands this capability substantially: for every wavelet, more than 440 trillion parameters are capable of being utilized, enabling unprecedented depth in signal resolution, contextual awareness, and pattern detection. This scale allows organizations to surface latent relationships that traditional analytics and signature-based systems routinely miss.
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They are ‘features’ not bugs. Once you realize that, everything else makes sense as to their inherent limitations.
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Also important to mention world (state) models can be used for mission critical applications in the Critical Infrastructure and Defense domains. Using Large Signal Model (LSM) technology is the key enabler. @DeepDecision @deep_labs @VectorForgeAI
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Replying to @akshay_pachaar
Thanks for sharing! I agree with you that LLMs lack the capacity to learn new things. This lack of continuous learning creates a host of problems for mission critical applications. ‘Context is everything’. Meaning humans primarily aren’t using language to determine the context to make decision, but all of the various signals they pick up during the day. Pure language based approaches will miss the most important signals that determine the everyday decisions we make. Decisioning systems, humans or machine, have to be able to adapt based on context.
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We are excited to announce the World's First Quantum-Secure AI Decisioning Platform. As quantum computing advances, the security of today's AI systems is at risk. VectorForge® proactively addresses this challenge with comprehensive post-quantum cryptography (PQC) integrated across our Data Integrity Validation Token (DIVT) infrastructure. This makes us the world's first AI platform inherently resistant to quantum threats, safeguarding your critical AI data and decision frameworks for the future. Trust Every Decision. Validate Every Data Point. vectorforge.ai/quantum
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Trust Every Decision. Validate Every Data Point.
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Powerful!
A great overview of the Course of Action (COA) capabilities of VectorForge. Trust Every Decision. Validate every Data Point. youtube.com/watch?v=viSrBXQS…
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VectorForge retweeted
Based on his CES presentation and what we see in the market, it’s clear the future of AI is being redefined faster than we imagined. #AI #Innovation @VectorForgeAI
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A great overview of the Course of Action (COA) capabilities of VectorForge. Trust Every Decision. Validate every Data Point. youtube.com/watch?v=viSrBXQS…
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