Thirty years ago, the landscape of tech startups was a different realm, where a strong technical background was not just an advantage, it was a necessity. Building a software application or platform was a complex endeavor, often out of reach for non-technical founders.
But the 90s are gone, taking clunky tech and convoluted development processes with them. Today, anyone with a good idea can overcome technical barriers, decode tech jargon, and build a successful tech startup, regardless of their background.
More effective development patterns, versatile funding options, and better infrastructure have all made it easier for non-tech founders to get into the startup game. But it is still important to bridge the gap between non-tech founders and the tech experts whom they work with.
Since Siri debuted on iOS in 2010, we’ve seen a slew of other voice-driven AI assistants. Alexa, Google Assistant, and Cortana have become household names.
At the same time, smart speakers have become ubiquitous in households and workplaces, making voice-driven computer human interaction commonplace. The result is that over 40% of people in the US now use voice search at least once per day, and that number is only likely to rise.
In the previous article, we discussed some key concepts, such as different markets and their characteristics, trading software, and chart visualizations of the market.
In this article, I would like to dive a little more into the technical aspects of algo trading and discuss the usage of public APIs.
Generally speaking, one could have only two ways of interacting with trading software: manual or automatic.
Manual ways include:
Web interface
Mobile application
Phone calls to your broker representative (it is still possible for stock markets, yes)
Strategic planning is critical for organizations to set their long-term goals, allocate resources, and make informed decisions. In today's rapidly changing business landscape, the influence of artificial intelligence (AI) and agile management methodologies on strategic planning has become increasingly significant. This article explores the benefits and implications of integrating AI and agile methodologies into strategic planning. Additionally, it examines the feasibility of using AI for employee training and its impact on organizational reality.
In my previous article, I highlighted the seamless deployment process of Rails 7 applications to AWS using MRSK and GitHub Actions. With four applications already in production, all managed by MRSK, we have come to appreciate its simplicity, centralized configuration, and developer-friendly approach. Having gained such positive experiences with MRSK on our newer projects, I decided to transition one of our Rails 6 applications from Capistrano to MRSK for deployment.
