Ed Investing Chief

Growth| Governance| Guidance| History| Crowd|. Not Financial advice. PharmBoy. Sow seeds, watch them grow. Prune

[Ed Investing Chief @ChiefEhe]

BE READY $PLTR

🇺🇸🐐GOAT 🐐🇺🇸

[Ed Investing Chief @ChiefEhe]

Jensen Huang first X post: open models…

[Jensen Huang @JensenHuang]

For my first post, I’m sharing a letter @NVIDIA signed on why open models matter.

AI will transform every industry, power every company, and be built by every country.

Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.

The world needs both frontier closed models and frontier open models.

https://t.co/AUKzoQ5Ikb

[Palantir @PalantirTech]

Twenty years ago, Palantir was a new entrant.

Today, we stand with some of tech’s biggest and emergent players to reject a future where a select few closed, frontier models rule them all.

Sovereignty and prosperity require American leadership in a strong open-weight AI ecosystem that strengthens competition, keeps customers in control, and drives the benefits of ingenuity across the economy.

[Chad Wahlquist @chadwahl]

I am working on a demo for next week and have never been more excited about what we are doing at Palantir.

Absolutely wild the pace that we are moving, I literally learned about 3 new products in the last 2 days and they are blowing me away. FDEs built these products at the edge and I am just finding out they exist. That is FDE'ing.

Seeing the reality of how this compounds because there is no friction, there is no long PM process or approvals, there is only delivering for customers, not next week, not next month......NOW.

[Gokarp @PLTRs_Palantir]

Joint ALL DOMAIN Command & Control
JADC2

All Domains
Land
Air
Sea
Space
Cyber

[Chad Wahlquist @chadwahl]

Oh I love earnings season 🚀

“higher levels of production and more stable and more optimized schedules at the mills, thanks to our work with Palantir, we are going to continue to bring these costs down.”

What do we do? Deliver Outcomes

[Eliano A Younes @eliano]

Palantir products and engineers have changed the course of history

[Gokarp @PLTRs_Palantir]

Who likes TACOS???
Whose hungry???

Shout out Talkin Tacos Gang @DeepValue47 @JackPrescottX @AndyRenfrew @jawwwn_

The Air Force has a RFI out for Tactical Air Traffic Control (ATC) Command and Control (C2) System AKA
TACOS 🌮

Key System Capabilities:
-The desired TACOS solution must deliver an integrated, scalable suite of capabilities as a survivable, expeditionary, and interoperable C2 platform providing reliable ATC services in support of Agile Combat Employment (ACE). The system shall provide, at minimum, the following capabilities:

Integrated Data Fusion Engine: (Smell that?)
-TACOS shall operate as a sensor-agnostic, Multi-Level Secure (MLS) data fusion engine that ingests, correlates, and fuses inputs from organic and non-organic sources into a single, unambiguous track per object and a low-latency Single Integrated Air Picture (SIAP). Source data shall include Primary and Secondary Surveillance Radar (PSR/SSR), ADS-B, Mode S and Mode 5 Identification Friend or Foe (IFF), Tactical Data Links (TDLs) such as Link 16 via JREAP, Counter Unmanned Aircraft System (C-UAS) tracks, and meteorological feeds, delivered in standard ATC formats including ASTERIX and Common Digitizer Model 2 (CD-2).

-The engine shall scale from a minimum of three to as many as twelve external radar sources and shall process the SIAP across multiple classification levels—operating on data at UNCLASSIFIED and SECRET//NOFORN and permitting designated workstations to run at SECRET//REL or UNCLASSIFIED while the overall system operates at SECRET//REL US.

-Fusion performance and resilience shall serve as core system capabilities. The fusion engine shall maintain track-processing latency within a sub-second threshold while minimizing duplicate-track generation. Simultaneously, an adaptive tracking filter shall dynamically weight sensor inputs based on real-time signal quality, track history, and localized electronic-warfare (EW) threat indicators to mitigate spoofed, jammed, or degraded feeds.

-To support rapid, expeditionary employment without requiring source-code or pre-loaded database modifications, the system shall autonomously build a self-configuring geographic grid at initialization. During this initialization, the system shall convert sensor-relative coordinates into a common, three-dimensional WGS-84 frame and project them onto an adaptation-defined local stereographic plane.

-Prior to fusion, the system shall time-align heterogeneous sensor updates using network- or Global Positioning System (GPS)-disciplined precision time. Furthermore, the system shall dynamically compute localized barometric and altimeter corrections from live meteorological data to produce continuous Mean Sea Level (MSL) altitude, eliminating reliance on static, tile-based adaptation databases.

-The fused picture shall be made coherent and shareable for both the operator and the wider force. The engine shall associate and bind each aircraft’s 24-bit ICAO Mode S address, Mode 3/A beacon code, and TDL track designators (including Link 16 Track Numbers) into a single track data block, group closely spaced military aircraft into labeled formation tracks while still processing their individual sub-tracks and overlay multi-level precipitation derived from surveillance inputs without degrading track processing.

-The system shall further consolidate sensor data into a tactical picture for distribution over TDLs and inclusion in the Common Tactical Picture, and shall gracefully manage sensor overload by shedding the most distant reports first so that continuous tracking, ATC sequencing and separation, and Air Base Point Defense cueing are preserved.

[Gokarp @PLTRs_Palantir]

Palantir Live, In-Person Instructor Led Official Trainings, Assessments, and Certifications

$16M secured for 4 days of work
PTFB

[Gokarp @PLTRs_Palantir]

Former Ukrainian Defense Minister Mykhailo Fedorov said that Palantir CEO Alex Karp had called him and proposed launching a joint project, speaking during a briefing on July 16.

[anand mahindra @anandmahindra]

Alex Karp’s CNBC interview is going to be widely discussed and debated.

My initial take on it:

Some will call Alex’s comments self-serving but there is an underlying argument he makes which I think is worth taking seriously: AI has three layers. Compute. Model. Application.

He argues that critical infrastructure doesn’t run on a model alone, that it needs an application layer sitting on top.

I think he’s right about the stack. I made a version of this argument in my recent letter to TechM’s shareholders this year: AI is like today’s smartphone: remarkable technology, but indispensable only because of the apps and experiences built on top of it. The ecosystem determines who creates lasting value, not the chip or the model underneath.

To be clear, I still believe India should pursue sovereign frontier model development. But if Karp’s hypothesis is right, and the model layer is commoditising, then the verticalization of the compute, models and applications needs to happen at the same time.

For AI services, from his arguments, it appears the more durable commercial and strategic edge is the application layer: model-agnostic, built on whichever open model fits best, carrying decades of enterprise workflow knowledge that no model provider owns.

As Karp says, the application layer “takes a large language model & makes it safe and precise…Everyone gets to ask the basic questions: who owns the data, where is it cashed, are the prompts secure, is this being transferred to you?” And “critical infrastructure does not run these models without an application layer.”

And this criticality is where the stakes are highest: defence, classified programs, regulated industries, where control over data, auditability and governance is non-negotiable, whichever model happens to sit underneath.

The application also has to enable business enterprises to preserve their ‘alpha.’

That’s where I truly believe AI service companies have the edge. Not necessarily in owning the model, but in owning what sits above it.

I’m keen to hear other reactions to his interview…

[Ed Investing Chief @ChiefEhe]

@farzyness @PalantirHotline Welcome the revolution $PLTR

[Cassandra Unchained @michaeljburry]

Staying married, a happy household, evidence of the parents working hard, childhood sports and watch all competitions, lots of hugs, reward merit, punish only egregious misbehavior, don't yell, restrict social media, monitor messages through 8th grade, the real expectation is college and academic excellence without pressure from parents, get children reading books early, no pacifiers, respond to needs not wants, babies sleep on their own through the night by 6 months, identify develop and support any talent or aptiude, one sport after age 10 is ok, communicate openly and easily with kids through grade 12, allow mistakes, and leave them alone in college. And then hope.

[Ed Investing Chief @ChiefEhe]

@stwboerse This is the voice of American business $PLTR

[Ed Investing Chief @ChiefEhe]

Great to hear $PLTR

[Kris Patel 🇺🇸 @KrisPatel99]

$PLTR $NVDA

Only way we're going to win in AI is Open Source.

Closed source models like Anthropic and OpenAI are desperately trying to create a regulatory moat to maintain their companies market value since their increasingly commoditized product is being supplanted by Opensource.

The key is that Opensource is how the entire ecosystem grows and becomes a net benefit to the entire US tech economy.

[Yahoo Finance @YahooFinance]

“There is no one, no company that has a moat like Karp and Palantir. And I think those that think that because of Anthropic or because of the overall market that in some way is going to eat into Palantir’s moat, I think that’s just way wrong,” Wedbush Securities’ @DivesTech says.

[amit @amitisinvesting]

BREAKING: Palantir $PLTR and Nvidia $NVDA expand their partnership to deliver sovereign AI for the US government and critical infrastructure agencies.

- The Partnership enables agencies to deploy, customize, and post-train NVIDIA Nemotron models on proprietary data.

- Combines NVIDIA AI infrastructure with Palantir platforms for sovereign, mission-critical AI.

- Gives customers control over data, IP, model weights, auditability, authorization, and post-training.

Once again, no matter what the model is…Palantir provides the infrastructure that makes any model operational to enable transformation within an enterprise.

Alex Karp: “Combining Palantir infrastructure with NVIDIA’s AI and Nemotron models will allow the U.S. government to unleash the full power of LLMs while removing the underlying security risks and rational concerns around proprietary insights migrating into the weights of closed models. Moreover, many of our US clients are already using these models, including multiple supporting critical US infrastructure — both private and public — and this will facilitate their radical expansion.”

Jensen Huang: “Open source AI is foundational to national security, public safety and U.S. technology leadership. Palantir’s Nemotron-powered intelligent engine shows how open models can strengthen America’s leadership in AI — giving U.S. government agencies a secure, customizable and fully controlled foundation to build mission-critical AI systems in support of national security.”

[Jawwwn @jawwwn_]

Alex Karp shares Palantir’s secret to sales:

“We hope you go to an LLM company.”

“No matter how bad this conference is, we could never sell you like they’ll sell you, which is—giving you something that makes you feel smart while your business goes out of business.”

“You’re going to go home feeling poorer and less safe.”

“You’ll buy the product, and pay a lot in tokens, and it’s going to be very hard to understand how it helps you.”

“But investors will know you’re smart.”

“Feel free to go learn about that and you’ll find: there’s a myriad of problems these models solve, and an even bigger amount of problems they create.”

[Wealthmatica @wealthmatica]

The $ZETA x $PLTR partnership is more significant than I first thought...

Snowflake does not play a hand in this conversation.

In reality, the ZDC (Zeta's data cloud) will be re-built on-top of Foundry, thus merging their Ontology with Zeta’s SuperGraph. This is enterprise intelligence on steroids, I'm not kidding.

Let’s start at the top.

To understand the direction of the enterprise stack you must look to the foundational layer of data ingestion, specifically down to the classification of the data. The enterprise stack can be broken into two core layers of intelligence:

- Operational intelligence (supply-side data)

- Consumer intelligence (demand-side data)

Operational data can be defined as the objects, employees and sequences that inform the enterprise of what their business is doing. On the other hand, you have consumer systems collecting signals, interactions and sales data establishing how business is performing. These are distinctly two different sides of the same enterprise brain.

Remember this for later in this post.

Originally I suspected due to the timely announcement of the Snowflake OSI partnership, $ZETA and $PLTR would utilize the joint development bridge designed by $SNOW to facilitate this relationship. No, I was wrong.

It’s 100X better.

$ZETA will indeed be re-architecting its core cloud database on top of $PLTR’s Foundry. This means, all of Zeta’s current clients will likely routed through this ecosystem unless they opt to utilize other cloud platforms. This may seem confusing, but it’s actually expected, as $ZETA is an agnostic provider after all.

The move to Foundry has several benefits, both for $ZETA and $PLTR. But ultimately, the real winner here is the enterprise client. Put a pin in that, we will come back to it at the end of this post.

Walking through how this will work…

View this partnership as the unification of two sides of the same brain. Except, this is the brain which produces enterprise grade intelligence. From operational intelligence, to consumer and business intelligence – through this agreement, the enterprise will create outcomes it has never obtained before.

$ZETA still owns their proprietary data-rails. Think Disqus, LiveIntent, Marigold, etc. On the flip side of the coin, $PLTR still owns the operational relationship with the enterprise – ingesting millions of raw data-points in real-time. What becomes shared, is the Intelligence layer.

You see, $ZETA has produced a “Consumer-like Ontology” called the SuperGraph. In Essence, a massive profile database enriched by real-time signals of intent and ID touch-points for 552M global people – these are proprietary, nobody else can produce this data. In this, $ZETA has created best-in-class business intelligence for marketing purposes when paired with an enterprise client datasets. This is where $PLTR comes in…

$PLTR has produced the world class “Digital Twin” ontology for government/enterprise operational applications. Ingesting millions of raw, unstructured and real-time data points funnelling them into Foundry. It is in this practice, $PLTR is able to produce operational intelligence, actioning insights, directives, or optimizations for an enterprise – thus becoming their native real-time operating system. However, something has been missing for both $ZETA and $PLTR.

$ZETA produces demand-side intelligence.

$PLTR produces supply-side intelligence.

The ultimate enterprise stack would consist of an intelligence generation mechanism that would be informed not only from the demand-side, but also the supply-side. Therefore creating a holistic approach to intelligence generation.

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[Zeta @ZetaGlobal]

Big news: Zeta Global and @PalantirTech announced a strategic partnership to build a unified data and AI infrastructure for the future of marketing.

By combining Palantir's AI infrastructure with Zeta's intelligent decisioning and trusted data, we're creating a new standard for data-driven, agentic marketing.

Palantir will support Zeta’s go-to-market efforts to bring this vision to eligible Palantir Foundry customers, helping enterprises connect operational intelligence, customer intelligence, and marketing execution on a unified foundation.

With Zeta's Data Cloud rearchitected on Palantir Foundry, Athena by Zeta™ will be able to draw on richer enterprise data and turn that intelligence into real-time decisions and measurable outcomes at enterprise scale.

As Athena becomes the operating system and infrastructure powering our customers' marketing technology stacks, this partnership creates a powerful foundation for the future of enterprise growth.

Read more: https://t.co/zCdGEKSS3T