ChatBot is a platform that lets you create your own chatbots with no programming skills.
Design smooth conversational experiences to build better relationships with your customers. Send dynamic responses that encourage customers to chat and interact. Mix and match text, images, buttons, and quick replies to show off your brand, products, and services.
Use ChatBot on different platforms and channels using one-click integration (Facebook Messenger, Slack, LiveChat, WordPress, and more). Connect your chatbot to just about anything you can think of using open API, webhooks, and Zapier.
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Google Cloud TPU might be a bit more popular than ChatBot. We know about 5 links to it since March 2021 and only 4 links to ChatBot. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Intercom, Solvvy, chatbot.com, helpshift etc the list goes on. Source: over 1 year ago
Engineering is definitely going to be the harder path to take to get into Ai but also more lucrative. I started off in UX design which is in high demand right now, everyone is looking for designers. Many places offer quick design certificates but do your research before picking one. Build up a portfolio of work that you've done. Play around with bot builder programs like IBM's Watson. Check out chatbot.com, they... Source: over 2 years ago
So my tips for you would be: create a personal website (I like squarespace), learn how add a bot to your site using programs like chatbot.com, start networking (LinkedIn is helpful), start building a portfolio of case studies, watch lots of youtube videos. Source: over 2 years ago
Dialogflow CX is the most advanced dialog model with a combination of intents, events and a state machine for every flow. However the interface is somewhat limited and a lot of features are expected to be done in your fulfilment backend with code that are available in the gui in watson or chatbot.com if you run your own backend server anyways and want to invest a bit in building the best solution possible, this... Source: almost 3 years ago
According to https://cloud.google.com/tpu, each individual TPUv3 has 420 Teraflops, and TPUv4 is supposed to double that performance, so if that guess is correct, it should take a few seconds to do inference. Quite impressive really. - Source: Hacker News / about 2 years ago
You can also rent a cloud TPU-v4 pod (https://cloud.google.com/tpu) which 4096 TPUv-4 chips with fast interconnect, amounting to around 1.1 exaflops of compute. It won't be cheap though (excess of 20M$/year I believe). - Source: Hacker News / over 2 years ago
Actually, that's done with TPUs which are more efficient: https://cloud.google.com/tpu. Source: almost 3 years ago
TPU training uses Google silicon and is thus a true deep learning alternative to Nvidia. Source: almost 3 years ago
The server choice really depends on how much CPU and RAM the requests take, how many users will be hitting the server, etc. You can start with a $5/month Digital Ocean server (or AWS or Google) and see if that works for you. Or you can outsource the server administration to Amazon or Google if you don't want to deal with it or need specialized tpu hardware. Source: about 3 years ago
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