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Software is dead. Every industry is going to be run by an Ontology. Predictions. by 2030: 1. $HIMS ontology dominates healthcare. 2. $SPOT ontology dominates media. 3. $DUOL ontology dominates education. 4. $PLTR ontology dominates industry. 5. $TSLA ontology dominates autonomy.

Antonio Linares

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I’m betting my entire net worth on 5 predictions: (from $6.34 $PLTR investor) → $DUOL = dominates global education. → $HIMS = $1T giant in 10 years. → $PLTR = $2T as AI ontology grows. → $AMD = crushes NVIDIA via chiplets. → $META = $5T AI giant. $HIMS $2000 thesis. 👇

I’m betting my entire net worth on 5 predictions: (from $6.34 $PLTR investor) → $DUOL = dominates global education. → $HIMS = $1T giant in 10 years. → $PLTR = $2T as AI ontology grows. → $AMD = crushes NVIDIA via chiplets. → $META = $5T AI giant. $HIMS $2000 thesis. 👇

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I’m betting my entire net worth on 5 predictions: (from $6.34 $PLTR investor) → $DUOL = dominates global education. → $HIMS = $500B giant in 5 years. → $PLTR = $2T as AI ontology grows. → $AMD = crushes NVIDIA via chiplets. → $META = $5T AI giant. $AMD $2000 thesis. 👇

I’m betting my entire net worth on 5 predictions: (from $6.34 $PLTR investor) → $DUOL = dominates global education. → $HIMS = $500B giant in 5 years. → $PLTR = $2T as AI ontology grows. → $AMD = crushes NVIDIA via chiplets. → $META = $5T AI giant. $AMD $2000 thesis. 👇

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I’m betting my entire net worth on 5 predictions: (from $6.34 $PLTR investor) → $DUOL = dominates global education. → $HIMS = $500B giant in 5 years. → $PLTR = $2T as AI ontology grows. → $AMD = crushes NVIDIA via chiplets. → $META = $5T AI giant. $AMD $2000 thesis. 👇

I’m betting my entire net worth on 5 predictions: (from $6.34 $PLTR investor) → $DUOL = dominates global education. → $HIMS = $500B giant in 5 years. → $PLTR = $2T as AI ontology grows. → $AMD = crushes NVIDIA via chiplets. → $META = $5T AI giant. $AMD $2000 thesis. 👇

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I’m betting my entire net worth on 5 stocks: (from $6.34 $PLTR investor) → $DUOL = dominates global education. → $HIMS = $1T in 15 years. → $PLTR = $2T as AI ontology grows. → $AMD = crushes NVIDIA via chiplets. → $META = $5T AI giant. $AMD $2000 thesis. 👇

I’m betting my entire net worth on 5 stocks: (from $6.34 $PLTR investor) → $DUOL = dominates global education. → $HIMS = $1T in 15 years. → $PLTR = $2T as AI ontology grows. → $AMD = crushes NVIDIA via chiplets. → $META = $5T AI giant. $AMD $2000 thesis. 👇

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I’m betting my entire net worth on 5 stocks: (from $6.34 $PLTR investor) → $DUOL = dominates education. → $HIMS = $1T giant in 10 years. → $PLTR = $2T as AI ontology grows. → $AMD = crushes NVIDIA via chiplets. → $META = $5T AI giant. $AMD $2000 thesis👇

I’m betting my entire net worth on 5 stocks: (from $6.34 $PLTR investor) → $DUOL = dominates education. → $HIMS = $1T giant in 10 years. → $PLTR = $2T as AI ontology grows. → $AMD = crushes NVIDIA via chiplets. → $META = $5T AI giant. $AMD $2000 thesis👇

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Christian Darnton is betting his entire net worth on 5 predictions: 1. $DUOL = $1T dominating global education. 2. $HIMS = $400B in 5yrs 3. $PLTR hits $2T as AI ontology grows 5. $AMD crushes NVIDIA via chiplets.

Christian Darnton is betting his entire net worth on 5 predictions: 1. $DUOL = $1T dominating global education. 2. $HIMS = $400B in 5yrs 3. $PLTR hits $2T as AI ontology grows 5. $AMD crushes NVIDIA via chiplets.

Antonio Linares

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I’m betting my entire net worth in 2026 on these 4 predictions - (from early $6.34 $PLTR investor): → $DUOL hits $1T dominating global education. → $HIMS = a $500B healthcare giant in 5 years. → $PLTR hits $2T as AI ontology grows. → $AMD crushes NVIDIA via chiplets. 👇

I’m betting my entire net worth in 2026 on these 4 predictions - (from early $6.34 $PLTR investor): → $DUOL hits $1T dominating global education. → $HIMS = a $500B healthcare giant in 5 years. → $PLTR hits $2T as AI ontology grows. → $AMD crushes NVIDIA via chiplets. 👇

Christian Darnton

301,110 Aufrufe • vor 9 Monaten

everyone gave up on $hims in february 2026 the stock is up ~3x since $hims isn’t a glp-1 company. it’s a healthcare ontology. $2,000/share intrinsic value by 2030

everyone gave up on $hims in february 2026 the stock is up ~3x since $hims isn’t a glp-1 company. it’s a healthcare ontology. $2,000/share intrinsic value by 2030

Antonio Linares

53,475 Aufrufe • vor 2 Monaten

I’m betting my entire net worth in 2026 on 4 predictions: (from early $6.34 $PLTR investor) → $DUOL hits $1T dominating global education. → $HIMS = a $500B giant in 5 years. → $PLTR hits $2T as AI ontology grows. → $AMD crushes NVIDIA via chiplets. $DUOL $2000 thesis. 👇

I’m betting my entire net worth in 2026 on 4 predictions: (from early $6.34 $PLTR investor) → $DUOL hits $1T dominating global education. → $HIMS = a $500B giant in 5 years. → $PLTR hits $2T as AI ontology grows. → $AMD crushes NVIDIA via chiplets. $DUOL $2000 thesis. 👇

Christian Darnton

120,349 Aufrufe • vor 6 Monaten

I’m betting my entire net worth in 2026 on 4 predictions: (from early $6.34 $PLTR investor) → $DUOL hits $1T dominating global education. → $HIMS = a $500B giant in 5 years. → $PLTR hits $2T as AI ontology grows. → $AMD crushes NVIDIA via chiplets. $DUOL $2000 thesis. 👇

I’m betting my entire net worth in 2026 on 4 predictions: (from early $6.34 $PLTR investor) → $DUOL hits $1T dominating global education. → $HIMS = a $500B giant in 5 years. → $PLTR hits $2T as AI ontology grows. → $AMD crushes NVIDIA via chiplets. $DUOL $2000 thesis. 👇

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120,227 Aufrufe • vor 8 Monaten

I’m betting my net worth in 2026 on 4 predictions - (from early $6.34 $PLTR investor): → $DUOL hits $1T dominating global education. → $HIMS = a $500B giant in 5 years. → $PLTR hits $2T as AI ontology grows. → $AMD crushes NVIDIA via chiplets. $HIMS $2000 PT thesis👇

I’m betting my net worth in 2026 on 4 predictions - (from early $6.34 $PLTR investor): → $DUOL hits $1T dominating global education. → $HIMS = a $500B giant in 5 years. → $PLTR hits $2T as AI ontology grows. → $AMD crushes NVIDIA via chiplets. $HIMS $2000 PT thesis👇

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292,526 Aufrufe • vor 8 Monaten

everyone gave up on $HIMS in february 2026 the stock is up ~3X since $hims is a not a GLP-1 company, but a Healthcare Ontology $2,000/share intrinsic value by the year 2030

everyone gave up on $HIMS in february 2026 the stock is up ~3X since $hims is a not a GLP-1 company, but a Healthcare Ontology $2,000/share intrinsic value by the year 2030

Antonio Linares

105,325 Aufrufe • vor 3 Monaten

I’m betting my entire net worth in 2026 on 4 predictions - (from early $6.34 $PLTR investor): → $DUOL hits $1T dominating global education. → $HIMS = a $500B giant in 5 years. → $PLTR hits $2T as AI ontology grows. → $AMD crushes NVIDIA via chiplets. Duolingo thesis. 👇

I’m betting my entire net worth in 2026 on 4 predictions - (from early $6.34 $PLTR investor): → $DUOL hits $1T dominating global education. → $HIMS = a $500B giant in 5 years. → $PLTR hits $2T as AI ontology grows. → $AMD crushes NVIDIA via chiplets. Duolingo thesis. 👇

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$PLTR Sat down with Palantir CEO Alex Karp at Palantir's 9th AIPCon to discuss where software is going, why AI models need an ontology, what Palantir's message is around the war, and why value creation is the only way to survive. Thank you to Alex for taking the time!

$PLTR Sat down with Palantir CEO Alex Karp at Palantir's 9th AIPCon to discuss where software is going, why AI models need an ontology, what Palantir's message is around the war, and why value creation is the only way to survive. Thank you to Alex for taking the time!

amit

232,597 Aufrufe • vor 6 Monaten

biology<>AI is going to deliver most of the returns in the stock market I went long $pltr at $7, $amd at $4.2: this is way, way bigger breaks down into two buckets: read: $rxrx $naut $tem $cai $hims write: $ibrx $inkt $ngen $pbls most value accrues to the Ontology: $HIMS

biology<>AI is going to deliver most of the returns in the stock market I went long $pltr at $7, $amd at $4.2: this is way, way bigger breaks down into two buckets: read: $rxrx $naut $tem $cai $hims write: $ibrx $inkt $ngen $pbls most value accrues to the Ontology: $HIMS

Antonio Linares

77,485 Aufrufe • vor 3 Monaten

Alex Karp says the reason Palantir is so unique is because of their willingness to be "non-mimetic": "When the whole world said software had to be worthless—we built platforms that worked." "When the whole world said you couldn't extend it with FDEs—we built FDEs." "When the whole world is saying build AI slop without an ontology that allows you to put truths into the ontology and produce actual results—we stuck to our guns." "And what did we get? We got these results."

Alex Karp says the reason Palantir is so unique is because of their willingness to be "non-mimetic": "When the whole world said software had to be worthless—we built platforms that worked." "When the whole world said you couldn't extend it with FDEs—we built FDEs." "When the whole world is saying build AI slop without an ontology that allows you to put truths into the ontology and produce actual results—we stuck to our guns." "And what did we get? We got these results."

Jawwwn

77,558 Aufrufe • vor 4 Monaten

Microsoft has released an open-source tool that helps teams learn ontology design before choosing a knowledge graph platform. It is called Ontology Playground. The project is a fully static React app, which means it does not need a backend, account system, database, or hosted service to run. The goal is simple: Help people understand what goes inside a graph before they buy or build the graph database. Ontology Playground includes six pre-built domain ontologies: → Retail → Healthcare → Finance → Manufacturing → E-Commerce → Education Each one gives users a starting point for understanding entities, relationships, properties, and how domain knowledge gets structured. The app also includes a live visual designer, structured learning paths, hands-on labs, and RDF/XML export for Fabric IQ. Because it is static, it can be deployed almost anywhere. No backend. No vendor lock-in. No platform commitment upfront. This matters because many teams jump into knowledge graphs too early. They focus on the database first. But the harder question is usually: What should the graph actually know? Ontology Playground teaches that layer first.

Microsoft has released an open-source tool that helps teams learn ontology design before choosing a knowledge graph platform. It is called Ontology Playground. The project is a fully static React app, which means it does not need a backend, account system, database, or hosted service to run. The goal is simple: Help people understand what goes inside a graph before they buy or build the graph database. Ontology Playground includes six pre-built domain ontologies: → Retail → Healthcare → Finance → Manufacturing → E-Commerce → Education Each one gives users a starting point for understanding entities, relationships, properties, and how domain knowledge gets structured. The app also includes a live visual designer, structured learning paths, hands-on labs, and RDF/XML export for Fabric IQ. Because it is static, it can be deployed almost anywhere. No backend. No vendor lock-in. No platform commitment upfront. This matters because many teams jump into knowledge graphs too early. They focus on the database first. But the harder question is usually: What should the graph actually know? Ontology Playground teaches that layer first.

Ryan Hart

246,813 Aufrufe • vor 2 Monaten

Alex Karp says the reason Palantir was able to create FDEs and be so unique is because of their willingness to be "non-mimetic": "When the whole world said software had to be worthless—we built platforms that worked." "When the whole world said you couldn't extend it with FDEs—we built FDEs." "When the whole world is saying build AI slop without an ontology that allows you to put truths into the ontology and produce actual results—we stuck to our guns." "And what did we get? We got these results."

Alex Karp says the reason Palantir was able to create FDEs and be so unique is because of their willingness to be "non-mimetic": "When the whole world said software had to be worthless—we built platforms that worked." "When the whole world said you couldn't extend it with FDEs—we built FDEs." "When the whole world is saying build AI slop without an ontology that allows you to put truths into the ontology and produce actual results—we stuck to our guns." "And what did we get? We got these results."

Jawwwn

36,000 Aufrufe • vor 4 Monaten