The Friday AI hype firehose came right on schedule last week. Right before the weekend, the Financial Times reported that DeepMind co-founder Mustafa Suleyman and LinkedIn creator Reid Hoffman were seeking up to $675 million in funding for their startup Inflection, even though they have yet to release a product. Then the publication reported that Andreessen Horowitz, Marc Andreessen's venture capital firm, had led an investment of more than $200 million in generative AI company Character AI (which generates dialogue in the style of characters such as Elon Musk and Nintendo's Mario), launching the startup to a $1 billion valuation. The same day, Bloomberg reported that Stability AI, the parent company of the popular open-source Stable Diffusion, is already hunting for additional investment that would value the company at $4 billion. This is all in addition to my weighed-down email inbox, which by Friday was overflowing with subject lines like "Early Look at World's First Customer Support Platform Powered by OpenAI" and "Generative AI Content Creation App For Branded Enterprise Content" and "New ChatGPT-like Feature to Revolutionize Data-Driven Marketing."

I'm going to discuss and go through a full application that was built to explore: Serverless - Serverless is clearly still running on a server, but put simply it's using resources on demand, with AWS taking care of the infrastructure and servers. Event Driven Architecture - Going hand in hand with serverless is being an event driven architecture - because we only pay for what we use, having an application that has absolutely nothing running until it has to reactively process a message. We also will also see how separate components, or Microservices, can be separated by the Event Bus and could theoretically be developed by whole separate teams and Code Bases. Cloud Native Patterns - I've tried to include lot's of different use cases to show different patterns that can be used when building Cloud Native applications - from analytics, orchestration, etc The vehicle for this journey will be a Twitter Bot; an application that can be fully reactive but something that isn't bound by specific domain behaviours, and not complex to understand. The important part that you need to know is that Twitter has an API called the Account Activity API which can be configured to fire webhooks when any activity happens with a particular account. This means we will be sent events when receiving a mention for example - which is an ideal way to explore these technologies that has an internal and external domain. As everything should be built in my opinion, the infrastructure is specified with code, so the whole application from the actual code, to the setting up of infrastructure is from a single application built using the AWS Cloud Development Kit.

When it comes to designing user experiences with our systems, the less, the better. We're overwhelmed, to put it mildly, with demands and stimuli. There are millions of apps, applications and websites begging for our attention, and once we have a particular app, application and website up, we still are bombarded by links and choices. Artificial intelligence is offering relief on this front. User experience, driven by AI, may help winnow down a firehose of choices and information needed at the moment down to a gently flowing fountain.

We're overwhelmed, to place it mildly, with calls for and stimuli. There are tens of millions of apps, purposes and web sites begging for our consideration, and as soon as we've a specific app, utility and web site up, we nonetheless are bombarded by hyperlinks and decisions. Every single day, each hour, each minute, it is a firehose. Synthetic intelligence is providing reduction on this entrance. Person expertise, pushed by AI, could assist winnow down a firehose of decisions and knowledge wanted for the time being all the way down to a gently flowing fountain.

It's tough being an imagery analyst for the U.S. military: you're drowning in pictures and drone video, with more pouring in endlessly from the tons of sensors and cameras used on planes, ships and satellites. Sifting through it to find roadside bombs or missile components is a time-consuming challenge. That's why the Pentagon's blue sky research arm figures that cameras ought to be able to filter out useless information themselves – so you don't have to. Darpa announced yesterday that it's moving forward in earnest with a program to endow cameras with "visual intelligence." That's the ability to process information from visual cues, contextualize its significance, and learn what other visual data is necessary to answer some pre-existing question.