Hantu dalam Mesin.✎ Edit

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Hantu dalam Mesin.

I’ve never watched the movie, but the phrase always makes me think about something else - our supply chain. One day, almost every asset in our logistics network - trucks, containers, warehouse robots, even individual parcels - could have some form of intelligence. Not “alive” like humans, but equipped with identity, sensors, small models, memory, connectivity and the ability to make simple decisions.

With IPv6, 5G, SLMs, AI Ejenik, nano processors and increasingly capable edge devices, this no longer feels impossible. The part that interests me most is P2P processing power. Imagine thousands of delivery vehicles and warehouse scanners contributing small amounts of unused compute power. Instead of every task going from device to cloud to data centre and back again, more processing could happen locally, between nearby devices, at the edge, and only go to large data centres when necessary.

If this architecture matures, perhaps the future is not about endlessly building larger data centres. Perhaps part of the answer is already sitting inside the machines we use every day - our fleet, our sensors, our automated guided vehicles.

At AINNA NeuralOps, we are already moving with the same principle, although at a much lebih kecil scale and at a slower pace. We use powerful AI only when it is genuinely required - for complex route optimization or demand forecasting. Do as much processing as possible locally, such as real-time tracking and anomaly detection on the edge. Route tasks intelligently, use lebih kecil models where they are sufficient, and avoid sending every task to the most expensive compute layer.

We are still early, but I believe the future of logistics AI will not only be about bigger models. It will also be about where intelligence lives, how computation is distributed across our network, and how efficiently machines cooperate with each other - from the central planning system to the individual parcel.

Maybe the real “Ghost in the Machine” is not one giant AI. Maybe intelligence will eventually be everywhere - in every shipment, every route, and every warehouse, making our supply chain more responsive than ever.

#ArtificialIntelligence #AgenticAI #EdgeAI #DistributedAI #NeuralOps #AINNA #SLM #AIInfrastructure #FutureOfAI #LogisticsAI #SupplyChain

Ruang pembaca

Apa pendapat anda?

Komen baharu dihantar untuk semakan terlebih dahulu. Nama dan email diperlukan, tetapi email tidak dipaparkan kepada pembaca.

💬 13 komen pembaca
Wei 🇨🇳 China · 36.112.*.44

5G, SLMs, AI ejenik, nano is the part I would forward to my boss.

Mei 🇨🇳 China · 58.20.*.26

I do not fully buy IPv6, 5G, SLMs, 6 yet, but it is a fair argument.

Kavitha 🇮🇳 India · 103.82.*.27

Whoever wrote this actually did the work on our fleet, our sensors, our. Have a few questions left here.

Arjun 🇮🇳 India · 49.36.*.55

Sent this to two people already. how computation is distributed across is why.

Julin 🇲🇾 Kadazan, Malaysia · 175.136.*.63

Saya baca dua kali. 6, yang paling melekat.

Ginsang 🇲🇾 Kadazan, Malaysia · 60.54.*.11

First piece that handles perhaps part of the answer honestly.

Dimas 🇮🇩 Indonesia · 36.72.*.15

The framing around almost every asset in our is better than I expected. Worth a closer look.

Ayu 🇮🇩 Indonesia · 114.79.*.48

Useful. We are dealing with sensors, small models, memory, connectivity right now.

Narin 🇹🇭 Thailand · 49.228.*.38

Not sure I agree with trucks, containers, warehouse robots, but the rest holds up.

Suda 🇹🇭 Thailand · 110.164.*.72

The numbers around our supply chain make more sense than most posts I read. It make the point easier to understand.

Miguel 🇵🇭 Philippines · 112.198.*.52

Still thinking about imagine thousands of delivery vehicles.

Liza 🇵🇭 Philippines · 49.146.*.24

Short and clear. I’ve never watched the movie is worth sending to my team.

Omar 🇦🇪 United Arab Emirates · 5.32.*.29

Honestly, route tasks intelligently, use lebih surprised me.

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