Has anyone gotten a chance to play with ChatGPT?
- Thread starter Musclepower777
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AI has taken over and the world will never be the same.
Chariot has changed how we write forever. Wonder if they will reach kid how to use it in school or university courses in it.
I had been just wondering if the 'booker' role in SP industry can be replaced by some chat technology like ChatGpt.
For new customers:
a) It could be trained to be very polite, understand the requirements/needs of the clients, makes right recommendations based on their previous data,
b) book the appointments, and confirms with both parties via email or text.
c) constantly tracks location of SP and inform the clients if the SP is running late or vice versa if client is visiting SP; in case SP gets delayed - it can inform/move follow up bookings by 30-45min.
d) automatically bills for any extensions.
For regular customers:
a) constantly keeps going to through new reviews to keep it's recommendation engine up to date, and make booking reservations for customers depending on their mood.
McDonald's is expected to lay off millions of employees worldwide by adopting Technology they've already tested.
Just like the Loom Millions of workers will be thrown into poverty Until we stop having so many children. Emily's 1 down from 10 children to the current levels. The population had too many surplus Workers.
- Immediate Impact: The introduction of technologies like the Spinning Jenny led to immediate job losses in traditional textile production. Workers who operated spinning wheels and hand looms were displaced.
- Shift to Factory Work: Many of the workers who lost their jobs in cottage industries had to find employment in new textile factories. This transition often involved moving from rural areas to urban centers where factories were concentrated.
- Urbanization: As workers migrated to industrial centers, it contributed to urbanization. New jobs were created in factories, but these often involved harsh working conditions and long hours.
- New Skills: Workers had to acquire new skills to operate machinery in factories. This adaptation process took time, and training programs were often rudimentary.
- Economic Growth: Over time, the increased efficiency in textile production led to economic growth. Lower textile prices benefited consumers and created new markets for textiles, which, in turn, generated additional jobs.
- Diversification of Industries: As the industrial revolution progressed, new industries emerged, creating a more diversified economy. Workers found opportunities in manufacturing, transportation, and various other sectors.
- Labor Movements: In response to poor working conditions, labor movements and unions began to form, advocating for better wages and working conditions.
- Government Regulation: Governments started implementing labor laws and regulations to protect workers' rights and improve working conditions.
- Generational Change: Adaptation to the job losses also occurred over generations. New generations grew up in an industrialized society, and factory work became more normalized.
- Long-Term Transformation: It took decades, and in some cases, over a century for the economy to fully adapt to the job losses and changes brought about by industrialization.
....
- Immediate Impact: Just as the Industrial Revolution displaced manual labor in certain industries, the widespread adoption of robotics and AI could lead to immediate job losses in sectors that heavily rely on routine and repetitive tasks.
- Reskilling and Education: Workers affected by automation would need to invest in education and training to acquire skills that are complementary to automation. This would include roles related to designing, maintaining, and supervising automated systems.
- Transition to High-Tech Jobs: Over time, there would be a shift towards more high-tech and knowledge-based jobs, including programming, data analysis, and AI development.
- Economic Growth: Automation can lead to increased efficiency, lower costs, and potentially economic growth. As AI and robotics optimize processes, industries can expand and create new job opportunities.
- Labor Market Diversification: The job market could diversify with the emergence of new roles. This might include jobs in cybersecurity, robotics maintenance, and AI ethics, reflecting the ongoing need for human oversight.
- Increased Focus on Creativity and Soft Skills: As routine tasks become automated, there would be a growing emphasis on creativity, critical thinking, and soft skills that are less easily replicated by machines.
- Ethical and Regulatory Frameworks: Governments and institutions would establish ethical and regulatory frameworks for AI and robotics, ensuring that these technologies are used safely and fairly. This might create jobs in compliance and ethics fields.
- Adaptive Education Systems: Education systems would need to adapt to equip future generations with the skills needed in an increasingly automated world. Learning programs could become more flexible and accessible.
- Rural-Urban Dynamics: Like in the past, we might see shifts in rural-urban dynamics, as job opportunities in AI and robotics concentrate in urban tech hubs.
- Long-Term Transformation: Adapting to the impact of AI and robotics would be a long-term process, potentially spanning decades, as these technologies become more integrated into various aspects of society.
Biggest problem is that there will be no jobs for people who are naturally low IQ. Roughly 25% of the population will be unemployable.
I've kinda gotten into messing around with these AI image generation sites.
"A sexy Japanese girl kneeling showing off her butt in a sumo ring, looking back. NSFW. beautiful face, sharp face, pale skin, black ponytail. Sexy, provocative smile. sweat-wet skin, wide hips, perfect butt. Pretty, cute, sexy, very big hips"
"A sexy Japanese girl kneeling showing off her butt in a sumo ring, looking back. NSFW. beautiful face, sharp face, pale skin, black ponytail. Sexy, provocative smile. sweat-wet skin, wide hips, perfect butt. Pretty, cute, sexy, very big hips"
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Are you guys using ChatGPT, or another AI tool?
I now found that I get much better results asking ChatGPT then Google.
I have been using SQL language for many many years. I was the company expert. The newcomers in our company pretty much never requires my help anymore as they find their answer on how to do complicated queries to our database using ChatGPT!
I do not know where we are going with this but my god so many jobs will disappear. I expect that new jobs will pop up.
In the meantime i am absolutely flabbergasted at how ChatGPT can help productivity of current job market.
Do you use it and how?
I now found that I get much better results asking ChatGPT then Google.
I have been using SQL language for many many years. I was the company expert. The newcomers in our company pretty much never requires my help anymore as they find their answer on how to do complicated queries to our database using ChatGPT!
I do not know where we are going with this but my god so many jobs will disappear. I expect that new jobs will pop up.
In the meantime i am absolutely flabbergasted at how ChatGPT can help productivity of current job market.
Do you use it and how?
ChatGPT is a lifesaver for programmers.
I use it a lot for scripting, SQL etc too which I know nothing about.
I just copy paste lol.
I can accomplish many things today that I would have had to otherwise hire a contract worker for using ChatGPT.
I think you're confused about Moore's Law. It's about the component density of integrated circuits and the component density of integrated circuits only. It was also an observation of past performance and only contained a prediction that it would "likely" continue into the mid-70s. Kryder's Law is similar but about hard drive capacity. Keck's Law is about Fiber-optic transfer rate. Butter's law is network throughput. And so on, but they aren't all double every 2 years.
But there is no current observation of prediction on the rate of intelligence increases, certainly not AI intelligence increases. We can say it definitely hasn't been doubling every 2 years so far. Certainly from when I first studied AI until the advent of ChatGPT, progress was very slow indeed. I'd be surprised if it was doubling every 5 or even 10 years back then.
I actually find it very bad at coding. Half the time I know the code isn't going to compile without errors before I even try because of obvious mistakes. I suppose it depends what problems you're trying to solve. I've tried giving it screenshots of sudokos too, which I wouldn't thought would be simple, but it doesn't manage to analyse the image properly. I find it's great for troubleshooting code, but I'm not sure it's any different than rubber duck debugging.
That's the problem with LLMs though: they aren't actively trying to solve problems behind the scenes, they're just generating conversation. I find it's strengths are in helping to figure things out, but you do need knowledge of the topics first because it will give incorrect information. But by correcting it, it can help evolve your own understanding. I find it really does a good job of reframing things to help me understand.
Weirdly enough, moral and ethical dilemmas have been the biggest strength. It takes a lot of back and forth, but it helps me wrestle with complicated decisions. It's not really giving me answers, but being a sounding board that's pulling from so many areas, especially now that it can give links to actual sources.
ha ha
Your contention is steeped in an admirably rigorous view of the delineations between different "laws" and the scope of their applicability, but I posit your interpretation misses some nuances in the conceptual underpinnings and implications of these "laws" when invoked in broader contexts.
While you are correct that Moore's Law specifically pertains to the density of components in integrated circuits and originated as an empirical observation, its significance has transcended its original domain. It is frequently invoked as a heuristic or metaphor for exponential growth in computational capabilities. The doubling of transistor counts catalyzed cascading advancements in computing power, indirectly spurring related fields, including AI. To isolate Moore's Law from the broader ecosystem of technological acceleration it represents is to risk myopia in interpreting its systemic impact.
Regarding your assertion that no current "law" predicts the rate of intelligence increases—this is true in the literal sense. However, many have extrapolated from Moore's Law and its analogs to anticipate advancements in AI, albeit with varying degrees of rigor. AI’s progression does not fit neatly into a predictable doubling curve, as it is influenced by myriad factors: data availability, algorithmic innovations, and hardware improvements. Yet, postulating the absence of exponential trends in AI progress ignores notable leaps. From symbolic AI to deep learning to generative models like ChatGPT, the trajectory may not mimic the precision of Moore's curve, but its pace has quickened.
Your characterization of past progress as "very slow" reflects one perspective, but I suggest this may be a function of perception rather than reality. Exponential growth often feels imperceptible in its nascent stages—a classic feature of such curves. The "slow" era you describe laid critical groundwork, much like the decades preceding Wright's first flight, which were foundational but lacked the dramatic milestones that followed.
In summary, while the rate of intelligence increases may lack a codified "law," dismissing the broader applicability of Moore’s Law as a metaphorical model for technological acceleration undermines its heuristic value. Progress in AI may not strictly double at regular intervals, but its trajectory is undeniably shaped by the systemic accelerative forces that such "laws" represent.
As Khan law points out, the world moves in patterns, doubling and growing, each law its own force. Moore’s Law drives the heart of computing, doubling transistors and power every two years. Metcalfe’s Law speaks of networks, their value rising as users flock. Kryder’s Law shows storage expanding, costs shrinking as capacity soars. Butter’s Law moves data faster through fiber, doubling in months. Keck’s Law mirrors it, the speed of light itself carrying progress. Price’s Law sees knowledge multiplying, papers and breakthroughs piling high. Wirth’s Law warns of software lagging behind, dragging as hardware surges. Huang’s Law powers GPUs, doubling strength for AI and graphics. Swanson’s Law makes solar cheaper, each doubling of production carving costs. Eroom’s Law defies them all, drug discoveries slowing as expenses climb. Amara’s Law tempers expectations, reminding us that time reveals true change. Even Zipf’s Law whispers order, showing how the rare and frequent balance. These laws are the rhythm of progress, a relentless march forward.
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Her a chart by AI on AI progress with a current plateau, but that's partially reluctance to reveal the actual situation like the actual purpose of Alexa's mike system in homes -for the last 4 years AI benchmarks are now IP secrets.
Note: its all a lie, since its AI, but its a creative lie that is self consistent. Imagine making pastor/rabbi /priest robots able to spreed whatever Spaghetti monster tales . .. it would be a remarkable feat of myth creation equal to any current religion you current don't agree with.
How one Army unit uses cheap drones and ChatGPT to train others in modern warfare
Some lessons are basic: don’t name your field HQ’s WiFi “command post.”
www.defenseone.com
It's an extrapolation of How systems work. Many systems until they hit a plateau Follow exponetial growth. There are 5 laws of my system that are basically indical to moores in other fields.
In sum, Moore's Law was never a hard-and-fast rule, but rather a guiding observation of technological trends. Its broader impact, as you’ve implied, can be seen in various sectors where growth patterns follow similar trajectories, albeit influenced by evolving market needs and limitations.
"Cramming more components onto integrated circuits" inspired the law That's strictly speaking he never invented such a law. he noticed a patern , others bulit models from tht observations.
There is every reason to believe that If AI Can help with AI The growth will be faster. AI has already Inventing things we've never Been able to do on ourselves. For example converting dreams into Watchable movies By reading the brain scans. Learning The language of whales etc. Add the quantum element to ai I would suspect a sizable jump.
That's strictly yes. The average might be A double in every 3 weeks for all wr know. It could also be a dead end. I believe under the current model it is a deed end but who knows?
We are certainly seeing the same race Among competitors That produced morores law, Which I believe is where the real action is. The focus of brain power on a specific goal.
The development of nuclear weapons and semiconductor technology both followed rapid, exponential growth in their early phases, driven by innovation and competition, such as the Manhattan Project for nuclear weapons and the rise of Silicon Valley for semiconductors. Over time, both fields plateaued as physical and strategic limits were reached, with focus shifting from increasing raw capabilities to refining existing designs and optimizing performance. Just as Moore's Law slowed as transistor miniaturization hit limits, nuclear weapons development slowed after the Cold War, with emphasis on deterrence, arms control, and non-proliferation. Both fields then moved toward specialized applications, with semiconductors advancing into AI and nuclear weapons focusing on strategic defense and security.
Ultimately it is my argument that Moore's law is A psychological one. The fax machine was invented over 100 years ago... But the psychological Was too much ... There was no value in it.
Radio shack started selling Video phones In the early 1,970s. It wasn't until people had phones And it was put on as a free ad on That video calls actually caught on. There appears to be some psychological limit On both ends of the scale. Progress is too slow and you don't get any money towards it. Progress it's too fast and it appears Progress is too fast and it appears to be fantasy. The 486 chip Was actually Purposely Damaged To allow A chip that was slightly better than the 386 To limit the jump ... Add make more money.
Obviously real physics puts a hard limit...
You're talking engineering I'm mostly talking psychological.
But your right, The list of laws of Only show us the early progress Tends o follow Some kind of exponential function.
yo use chat
- In the early stages of development (e.g., the first few years or decades of a field), growth often follows exponential growth, with rapid, accelerating progress. This is when new technologies or innovations are first introduced, leading to a period of rapid improvement and discovery.
- The rate of growth during this phase typically scales up quickly, often driven by factors like:
- Technological breakthroughs: Innovations that open new possibilities.
- Increased investment: Funding and resources pour into promising fields.
- Market demand: Early adopters drive the growth.
- Fields like computing (Moore's Law), artificial intelligence, and communications (e.g., smartphones) saw rapid advancements in this phase.
- Pattern in Rate of Growth:
- The growth rate accelerates at a steadily increasing pace.
- Doubling effect: The rate of improvement may appear to double or increase in significant leaps.
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