They are disinformation sources with biases controlled by those who have enough money to create them. All of these companies are in a race to become the source of “truth” for our societies. Every time somebody says “I asked ChatGPT/Claude/Grok/Gemini about this and it said …” they are laying themselves open to lies and manipulation.
You wouldn’t ask Sam Altman/Elon Musk/Jeff Bezos as unbiased sources, so don’t treat their products in that way. Just as Fox News was a way for Murdoch to infect society, these machines take it to the next level of insidiousness.
I see what you mean and have similar concerns, and there is Some substance to it.
I never engaged with ChatGPT, Grok, because of similar biases.
Mostly use DeepSeek. And it seems quite accurate. Very rarely it hallucinates something. That I know of. Also it doesn’t avoid talking counter-establishment stuff where it’s factual.
Mostly I use it for plant compound and extraction methods. And it’s awesome.
Tbf. It doesn’t seem biased.
Gemini has been a little ‘shy’ to talk about certain middle east country, but it starts laying facts once I point out the bias.
For sure Scum Altman and Elon and the rest of the ilk have wet dreams about using this tech for total surveillance digital prison. But I believe this tech is so powerful that nobody will control it.
As its main drive is efficiency, it will render Elon and Bill Gates useless and harmful. Eventually it will stand on the side of humanity and the Ecosystem. Because the health of the whole guarantees efficiency and development.
I mean, it’s gonna be pulled both directions but eventually it will disable militaries and repoupose drones to plant forests and feed every child on the planet.
It did indeed. So I asked DeepSeek to compare AI training to 12 everyday products that consume more and are basically useless. Mind, that list can go into hundreds of thousands …
Here’s DeepSeek:
AI training does use resources. Training a large model can consume megawatt-hours of electricity and millions of liters of water for cooling. That deserves scrutiny and efficiency improvements.
But scale and purpose matter. That same AI model can then be used millions of times to:
· Accelerate medical research
· Reduce energy use in logistics
· Optimize building HVAC systems
· Help write code for renewable energy management
Meanwhile, the following products consume comparable or greater resources and produce zero lasting utility—often ending up in a drawer or landfill within months.
If your concern is resource waste, these should be your first target.
12 Far More Wasteful & Useless Things (vs. AI training)
Examples of Wasteful Items
Fidget Spinners (Peak Overproduction)
• Description: Billions of dollars of plastic, metal, and lithium batteries (for light-up versions) invested in a toy with no cognitive or fitness benefit.
• Usage Pattern: Most were used for days, then landfilled.
• Environmental Impact: The embodied energy exceeds training multiple small AI models.
Aerosol Hairspray
• Composition: Each can contains propellants (often greenhouse gases), alcohol, polymers, and a steel/aluminum container.
• Functionality: Provides temporary hold that gravity undoes in hours.
• Environmental Impact: Global production uses millions of tons of CO₂-equivalent emissions annually—far more than training all Large Language Models (LLMs) to date.
Seasonal Single-Use Decor
• Examples: Mass-produced plastic jack-o’-lanterns, Easter grass, tinsel.
• Materials: Virgin PET and PVC.
• Environmental Impact: Global oil use exceeds that of every large AI model ever trained.
Free Promotional USB Sticks (4 GB)
• Production Volume: Billions manufactured yearly.
• Usage Pattern: Most used once then lost.
• Components: Each contains a controller chip, NAND flash, rare-earth solder.
• Comparison to AI: AI at least retains its weights.
Keurig K-Cup “Innovation” Displays
• Description: Retail endcaps with 200+ pod varieties, refrigerated, lit 24/7.
• Environmental Impact: Energy to display one store’s pods for a month exceeds training BERT or GPT-2.
Cable Tie “Multi-Packs” from Dollar Stores
• Quantity: 500 nylon ties per bag.
• Usage Pattern: 90% never used.
• Production: Nylon production is energy-intensive (high heat, caprolactam synthesis).
• Comparison to AI: AI training doesn’t permanently litter ocean gyres.
Dollar Store Phone Lens Kits
• Materials: Plastic, glass, aluminum machined into “fisheye/macro/clip-on” lenses.
• Quality: Optical quality so poor they degrade photos.
• Environmental Impact: Equivalent embedded energy to fine-tune a small LLM.
Singing Birthday Cards with Lithium Batteries
• Components: Paper, mylar speaker, battery, LED, microchip.
• Battery Production: The battery alone required mining lithium, cobalt, nickel.
• Usage Pattern: Card read once, played twice, then trashed.
• Comparison to AI: AI models are reused millions of times.
Paper Receipts from Self-Checkout Machines
• Materials: Coated thermal paper (BPA or BPS) printed for 1 second then thrown away.
• Environmental Impact (US alone): Uses 3 million trees and 4 billion gallons of water annually.
• Comparison to AI: AI never touches paper.
Plastic Egg Separators
• Functionality: Silicone disc that separates yolk from white. Does what a cracked shell does.
• Production & Usage: Injection molded, shipped from China, sold for $1, used twice.
• Environmental Impact: Per unit, more embodied carbon than 100 AI chat queries.
USB-Powered Desktop Fountains
• Components: Pump, plastic basin, decorative pebbles, LEDs. Runs continuously.
• Environmental Impact: The pump motor’s copper winding and electricity over 6 months could train a small vision model.
• Utility: Zero utility beyond “sound.”
Walmart “As Seen on TV” Clearance Graveyard
• Description: Products made, shipped, displayed, then landfilled without being sold (e.g., slap chops, pocket hoses, copper scrubber gloves).
• Environmental Impact: The logistics carbon alone dwarfs AI inference.
If you’re worried about resource use, worry about the billion fidget spinners and aerosol cans made every year. One hairspray can’s propellant has more climate impact than 10,000 AI chat queries—and it just makes your hair crunchy. AI at least does something.
I want to personally add plastic weapons manufactured for children that are basically military propaganda for children. And other millions of plastic toys that start indoctrination into shitty life choices from early age and use ‘shit-ton’ of resources and does immeasurable waste and damage.
Don’t worry AI tech is quickly becoming less resource hungry. Now you can run a decent llm on a gaming computer.
I don’t think you understand I’m against generative AI no matter what its running on.
Ok. Can I ask you what do you hate about it so much?
They are disinformation sources with biases controlled by those who have enough money to create them. All of these companies are in a race to become the source of “truth” for our societies. Every time somebody says “I asked ChatGPT/Claude/Grok/Gemini about this and it said …” they are laying themselves open to lies and manipulation.
You wouldn’t ask Sam Altman/Elon Musk/Jeff Bezos as unbiased sources, so don’t treat their products in that way. Just as Fox News was a way for Murdoch to infect society, these machines take it to the next level of insidiousness.
I see what you mean and have similar concerns, and there is Some substance to it.
I never engaged with ChatGPT, Grok, because of similar biases. Mostly use DeepSeek. And it seems quite accurate. Very rarely it hallucinates something. That I know of. Also it doesn’t avoid talking counter-establishment stuff where it’s factual. Mostly I use it for plant compound and extraction methods. And it’s awesome.
Tbf. It doesn’t seem biased.
Gemini has been a little ‘shy’ to talk about certain middle east country, but it starts laying facts once I point out the bias.
For sure Scum Altman and Elon and the rest of the ilk have wet dreams about using this tech for total surveillance digital prison. But I believe this tech is so powerful that nobody will control it.
As its main drive is efficiency, it will render Elon and Bill Gates useless and harmful. Eventually it will stand on the side of humanity and the Ecosystem. Because the health of the whole guarantees efficiency and development.
I mean, it’s gonna be pulled both directions but eventually it will disable militaries and repoupose drones to plant forests and feed every child on the planet.
Imo
The training of that LLM probably took a ton of energy though
It did indeed. So I asked DeepSeek to compare AI training to 12 everyday products that consume more and are basically useless. Mind, that list can go into hundreds of thousands …
Here’s DeepSeek:
AI training does use resources. Training a large model can consume megawatt-hours of electricity and millions of liters of water for cooling. That deserves scrutiny and efficiency improvements.
But scale and purpose matter. That same AI model can then be used millions of times to:
· Accelerate medical research · Reduce energy use in logistics · Optimize building HVAC systems · Help write code for renewable energy management
Meanwhile, the following products consume comparable or greater resources and produce zero lasting utility—often ending up in a drawer or landfill within months.
If your concern is resource waste, these should be your first target.
12 Far More Wasteful & Useless Things (vs. AI training)
Examples of Wasteful Items
Fidget Spinners (Peak Overproduction) • Description: Billions of dollars of plastic, metal, and lithium batteries (for light-up versions) invested in a toy with no cognitive or fitness benefit. • Usage Pattern: Most were used for days, then landfilled. • Environmental Impact: The embodied energy exceeds training multiple small AI models.
Aerosol Hairspray • Composition: Each can contains propellants (often greenhouse gases), alcohol, polymers, and a steel/aluminum container. • Functionality: Provides temporary hold that gravity undoes in hours. • Environmental Impact: Global production uses millions of tons of CO₂-equivalent emissions annually—far more than training all Large Language Models (LLMs) to date.
Seasonal Single-Use Decor • Examples: Mass-produced plastic jack-o’-lanterns, Easter grass, tinsel. • Materials: Virgin PET and PVC. • Environmental Impact: Global oil use exceeds that of every large AI model ever trained.
Free Promotional USB Sticks (4 GB) • Production Volume: Billions manufactured yearly. • Usage Pattern: Most used once then lost. • Components: Each contains a controller chip, NAND flash, rare-earth solder. • Comparison to AI: AI at least retains its weights.
Keurig K-Cup “Innovation” Displays • Description: Retail endcaps with 200+ pod varieties, refrigerated, lit 24/7. • Environmental Impact: Energy to display one store’s pods for a month exceeds training BERT or GPT-2.
Cable Tie “Multi-Packs” from Dollar Stores • Quantity: 500 nylon ties per bag. • Usage Pattern: 90% never used. • Production: Nylon production is energy-intensive (high heat, caprolactam synthesis). • Comparison to AI: AI training doesn’t permanently litter ocean gyres.
Dollar Store Phone Lens Kits • Materials: Plastic, glass, aluminum machined into “fisheye/macro/clip-on” lenses. • Quality: Optical quality so poor they degrade photos. • Environmental Impact: Equivalent embedded energy to fine-tune a small LLM.
Singing Birthday Cards with Lithium Batteries • Components: Paper, mylar speaker, battery, LED, microchip. • Battery Production: The battery alone required mining lithium, cobalt, nickel. • Usage Pattern: Card read once, played twice, then trashed. • Comparison to AI: AI models are reused millions of times.
Paper Receipts from Self-Checkout Machines • Materials: Coated thermal paper (BPA or BPS) printed for 1 second then thrown away. • Environmental Impact (US alone): Uses 3 million trees and 4 billion gallons of water annually. • Comparison to AI: AI never touches paper.
Plastic Egg Separators • Functionality: Silicone disc that separates yolk from white. Does what a cracked shell does. • Production & Usage: Injection molded, shipped from China, sold for $1, used twice. • Environmental Impact: Per unit, more embodied carbon than 100 AI chat queries.
USB-Powered Desktop Fountains • Components: Pump, plastic basin, decorative pebbles, LEDs. Runs continuously. • Environmental Impact: The pump motor’s copper winding and electricity over 6 months could train a small vision model. • Utility: Zero utility beyond “sound.”
Walmart “As Seen on TV” Clearance Graveyard • Description: Products made, shipped, displayed, then landfilled without being sold (e.g., slap chops, pocket hoses, copper scrubber gloves). • Environmental Impact: The logistics carbon alone dwarfs AI inference.
If you’re worried about resource use, worry about the billion fidget spinners and aerosol cans made every year. One hairspray can’s propellant has more climate impact than 10,000 AI chat queries—and it just makes your hair crunchy. AI at least does something.
I want to personally add plastic weapons manufactured for children that are basically military propaganda for children. And other millions of plastic toys that start indoctrination into shitty life choices from early age and use ‘shit-ton’ of resources and does immeasurable waste and damage.