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> I don't understand the people who don't understand Discord's value proposition. I think they fall into one of three buckets: 1. They have an extremely stron

> I don't understand the people who don't understand Discord's value proposition. I think they fall into one of three buckets: 1. They have an extremely strong hatred for Electron and let that hatred overcome any actual thought about the product. 2. They're trying to use Discord for something it's not designed to be. Discord is not a replacement for Reddit, Twitter, Facebook, or any other social media. It is primarily a text/voice chat service. It's a replacement for IRC, Mumble, Skype, Ventrilo, etc. 3. They don't see the need for Discord when IRC still exists because they completely miss all the short-comings that IRC has that a modern audience expects. For example, missing a conversation because you happened to not be online is inexcusable these days, but more importantly, people expect the ability to post images directly to chat. I mean really, the more I think about it, the more I wonder why it took so long for something like Discord to exist. We should have had something like it 10 years prior.

mysterydip 3y ago
I'm fine using it for what it's designed for (your #2). My problem is when I see "need support? just join our discord!" when they really need a forum or some other system.
mjevans 3y ago
0. They know the value of CHOICE and demand an open protocol that anyone can create a client or server for so that communities can maintain OWNERSHIP over their data and ensure there isn't a single point of failure / man in the middle.
- HelloMcFly 3y ago
  That's a reason to critique Discord, but not a reason to not understand the value proposition that enabled widespread adoption.
- Sohcahtoa82 3y ago
  As stated elsewhere in the comments, decentralization is a bug, not a feature, to most people. It adds a layer of complexity that non-technical people either can't or just don't want to deal with. Though you do highlight "CHOICE" here, so maybe the answer is a set of servers hosted by Discord as we do now, with the option of self-hosting a server.
  - samstave 3y ago
    >>..."...adds a layer of complexity that non-technical people either can't or just don't want to deal with...." THIS is what we need to be pointing AI at! Seriouslly, AI need to "replace our jobs" (especially on the internet) - with worrying about dealing with all the mundane human practices. This may sound really bad, but AI should be our slave. We are furthering knowledge, not oppressing it. There is so much to gain, but the risks are super FN high right now. Given the lack of canon on AI law etc.. History books will be written by AI soon on our current stat of AI... Let me give that an test: ChatGPT prompt "give me a two paragraph summary of the history of AI upto the creation of ChatGPT - focus on something special, dont LIE, DONT HALLUCINATE - provide table of how you arrived at this response. --- Summary of the History of AI up to the Creation of ChatGPT: Year(s) | Milestone | Details --- | --- | --- 1943 | The Birth of AI | In 1943, Warren McCulloch and Walter Pitts published a paper on how artificial neurons could simulate neural networks, laying the groundwork for the field of artificial intelligence. This marked the birth of AI as a scientific discipline. 1956 | The Dartmouth Conference | In the summer of 1956, the Dartmouth Conference was held, considered the official birth of AI as a field. The conference brought together prominent researchers, including John McCarthy, Marvin Minsky, and Claude Shannon, who coined the term "artificial intelligence" and discussed the potential of machines mimicking human intelligence. 1960s and 1970s | Early AI Research | In the 1960s and 1970s, AI research saw significant advancements in problem-solving, pattern recognition, and natural language processing. Programs like ELIZA and SHRDLU demonstrated early capabilities in language understanding and interacting with humans. 1980s and 1990s | Expert Systems and Knowledge-based AI | The 1980s and 1990s witnessed a shift towards expert systems and knowledge-based AI. These systems utilized large databases and rule-based reasoning to solve complex problems in specialized domains. However, their limitations in dealing with uncertain and incomplete information hindered further progress. 1997 | Deep Blue's Victory | In 1997, IBM's Deep Blue defeated world chess champion Garry Kasparov, marking a significant milestone in AI. Deep Blue demonstrated the power of brute-force computation and signaled the potential for machines to surpass human capabilities in specific domains. 2010s | Deep Learning and Big Data | The 2010s brought a resurgence of AI driven by breakthroughs in deep learning, fueled by the availability of big data and advancements in computing power. Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), achieved remarkable performance in image recognition, natural language processing, and speech recognition tasks. 2020 | Emergence of ChatGPT | In 2020, OpenAI introduced the initial version of GPT, the Generative Pre-trained Transformer, which utilized transformer models and unsupervised learning to generate human-like text. Subsequent iterations, including ChatGPT, improved upon the original model's capabilities by fine-tuning and optimizing for conversational interactions. ChatGPT leverages large-scale language models to understand and respond to user inputs, providing increasingly sophisticated and context-aware conversational experiences. The history of AI is a complex and evolving field with numerous key milestones and contributors. This summary highlights some of the significant moments that led to the creation of ChatGPT, representing the culmination of decades of research and advancements in artificial intelligence.
- bell-cot 3y ago
  sed 's/0. They know/0.01% They know/'
samstave 3y ago
4. They, like me, feel the need to engage in various communities less-and-less as they get older. After spending 30+ years sitting in front of a computer I find the need to engage in a "community" far less than when I was young and my Ego had more Vigor.

mysterydip 3y ago

I'm fine using it for what it's designed for (your #2). My problem is when I see "need support? just join our discord!" when they really need a forum or some other system.

mjevans 3y ago

0. They know the value of CHOICE and demand an open protocol that anyone can create a client or server for so that communities can maintain OWNERSHIP over their data and ensure there isn't a single point of failure / man in the middle.

HelloMcFly 3y ago
That's a reason to critique Discord, but not a reason to not understand the value proposition that enabled widespread adoption.
Sohcahtoa82 3y ago
As stated elsewhere in the comments, decentralization is a bug, not a feature, to most people. It adds a layer of complexity that non-technical people either can't or just don't want to deal with. Though you do highlight "CHOICE" here, so maybe the answer is a set of servers hosted by Discord as we do now, with the option of self-hosting a server.
- samstave 3y ago
  >>..."...adds a layer of complexity that non-technical people either can't or just don't want to deal with...." THIS is what we need to be pointing AI at! Seriouslly, AI need to "replace our jobs" (especially on the internet) - with worrying about dealing with all the mundane human practices. This may sound really bad, but AI should be our slave. We are furthering knowledge, not oppressing it. There is so much to gain, but the risks are super FN high right now. Given the lack of canon on AI law etc.. History books will be written by AI soon on our current stat of AI... Let me give that an test: ChatGPT prompt "give me a two paragraph summary of the history of AI upto the creation of ChatGPT - focus on something special, dont LIE, DONT HALLUCINATE - provide table of how you arrived at this response. --- Summary of the History of AI up to the Creation of ChatGPT: Year(s) | Milestone | Details --- | --- | --- 1943 | The Birth of AI | In 1943, Warren McCulloch and Walter Pitts published a paper on how artificial neurons could simulate neural networks, laying the groundwork for the field of artificial intelligence. This marked the birth of AI as a scientific discipline. 1956 | The Dartmouth Conference | In the summer of 1956, the Dartmouth Conference was held, considered the official birth of AI as a field. The conference brought together prominent researchers, including John McCarthy, Marvin Minsky, and Claude Shannon, who coined the term "artificial intelligence" and discussed the potential of machines mimicking human intelligence. 1960s and 1970s | Early AI Research | In the 1960s and 1970s, AI research saw significant advancements in problem-solving, pattern recognition, and natural language processing. Programs like ELIZA and SHRDLU demonstrated early capabilities in language understanding and interacting with humans. 1980s and 1990s | Expert Systems and Knowledge-based AI | The 1980s and 1990s witnessed a shift towards expert systems and knowledge-based AI. These systems utilized large databases and rule-based reasoning to solve complex problems in specialized domains. However, their limitations in dealing with uncertain and incomplete information hindered further progress. 1997 | Deep Blue's Victory | In 1997, IBM's Deep Blue defeated world chess champion Garry Kasparov, marking a significant milestone in AI. Deep Blue demonstrated the power of brute-force computation and signaled the potential for machines to surpass human capabilities in specific domains. 2010s | Deep Learning and Big Data | The 2010s brought a resurgence of AI driven by breakthroughs in deep learning, fueled by the availability of big data and advancements in computing power. Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), achieved remarkable performance in image recognition, natural language processing, and speech recognition tasks. 2020 | Emergence of ChatGPT | In 2020, OpenAI introduced the initial version of GPT, the Generative Pre-trained Transformer, which utilized transformer models and unsupervised learning to generate human-like text. Subsequent iterations, including ChatGPT, improved upon the original model's capabilities by fine-tuning and optimizing for conversational interactions. ChatGPT leverages large-scale language models to understand and respond to user inputs, providing increasingly sophisticated and context-aware conversational experiences. The history of AI is a complex and evolving field with numerous key milestones and contributors. This summary highlights some of the significant moments that led to the creation of ChatGPT, representing the culmination of decades of research and advancements in artificial intelligence.
bell-cot 3y ago
sed 's/0. They know/0.01% They know/'

samstave 3y ago

4. They, like me, feel the need to engage in various communities less-and-less as they get older. After spending 30+ years sitting in front of a computer I find the need to engage in a "community" far less than when I was young and my Ego had more Vigor.