Something interesting is happening in programming. Andrej Karpathy recently coined the term "vibe coding" - you describe what you want in plain English, and an AI writes the code for you.If you've tried the current tools, you know they kind of work sometimes, but the vibes can go bad pretty quickly. The online reactions are predictably extreme: either "All devs are redundant!" or "Real coders write code!" The truth is somewhere in the middle. I want to discuss what does and doesn’t work right now, and share how I get the most out of the current tooling.

To secure your project, you need a thorough assessment and mitigation of every possible risk. Here is how to approach this mission. Note: This is part 2 of the 3-part series that will explore the pitfalls that developers of the Generative AI-based application need to know and try to mitigate. Part 1 — Understanding the Security and Privacy Risks Part 2 — Uncovering pitfalls and mitigations that affect the Security and Privacy Risks Part 3 — Navigating the Murky Waters of Generative AI Regulation Landscape (Coming) Introduction Have you ever wondered how risk assessment for generative AI applications differs from the risk assessment performed for other applications?

In This Blog Post, We Will Explore the Role of Innovation in Business Success and Ways to Implement it. Introduction You cannot achieve long-term sustainable success by relying solely on your current strategies and technologies. The world is dynamic and rapidly changing, and you need to change and adapt. Innovation is imperative to ensure long-term sustainability, enhance competitiveness, and drive business growth. In this post, we aim to help you understand the importance of innovation in achieving business success.

In this post we’ll review the paper Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction. Background Writing test cases for bugs is a critical yet tedious part of software development. How much developer time is spent on this? The authors analyze 300 open source Java projects and find that on average 28% of tests were added as part of a bug fix. Most existing automated test generation tools focus on maximizing code coverage rather than reproducing issues described in natural language [1].

Within a year, coding assistants like GitHub Copilot went from being sci-fi fantasy to an essential tool for developer productivity. Sure, they’re not always helpful, sometimes they’re downright misleading, but they’re getting better every day and traffic to Stack Overflow has been down by an average of 6% every month since January 2022 — make of that what you will. So how is AI being applied to other aspects of the software development lifecycle?

An overview of the main security and privacy considerations developers need to consider when building products that leverage Generative AI. Note: This is part 1 of a 3 part series that will focus on the main security and privacy aspects related to building applications that leverage Generative AI technology The Rise in Popularity of Generative AI Models Generative Artificial Intelligence (AI) has rapidly gained popularity and found its way into various applications, empowering products with its ability to generate realistic content such as images, videos, text, and even music.

In this post we look at the distribution of capital within different sectors of web3 protocols; E.g. dexes, bridges, lending, derivatives, etc. To gauge the competitiveness of these sectors, we turn to a trusted tool from the world of economics: the Herfindahl-Hirschman Index (HHI). The Herfindahl-Hirschman Index: A Measure of Market Concentration HHI is a measure of the level of competition among firms in a market, or in our case, protocols within a sector.

Atchai has been working with Cabinet Office in the UK to explore how machine learning and natural language processing technology can be applied to improve organisational knowledge transfer and ultimately to improve policy making. Our work received positive coverage in The Times with a quote from our CTO:

We have developed a technique to understand the dominant reasons for protests and demonstrations happening around the world. Our work builds on the ACLED dataset, a source that’s regularly quoted in the media and described by the Guardian as being “the most comprehensive database of conflict incidents around the world”. ACLED helpfully collects all political violence and protest events but only provides a text description of the event which makes it hard to cluster together events that have a common theme and ask questions such as “how many BLM protests are happening per week?

Algorithms have been choosing our fate for years. From automated mortgage decisions to dating apps assessing our compatibility with a potential mate, machines are running the show. In spite of this, the controversy over UK exam grades being predicted by an algorithm has led many to question our reliance on computers over human judgement. Many feel troubled by the concept of algorithms assessing whether a criminal is likely to reoffend. However, by helping tackle the deep-seated problem of unconscious bias in the judicial system, could they be working towards the greater good?

Health care professionals are the real heroes of the moment but there is an important role for data scientists to play in the fight against the pandemic that’s shaking the globe right now. Your first port of call should be the COVID-19 Open Research Dataset — released on 20th March by the White House and a coalition of leading research groups. I recommend heading over to the associated Kaggle competition where you can collaborate and build upon the work of other data scientists who have already made progress on cleaning and understanding the potential of this dataset containing over 29,000 academic papers related to COVID-19, SARS-CoV-2, and other coronaviruses.

We’re pleased to announce that Atchai has been appointed as a supplier on the new government procurement framework for innovative technology - Spark DPS. CompleteFlow is our product for intelligent automation and conversational AI. It is now available with both cloud and on-premises hosting on Spark. If you’re looking to leverage conversational AI, machine learning or NLP technology in government or the public sector then please contact us in the first instance and we can advise on solutions and procurement options.

MythX (previously Mythril) recently made the decision to drop their custom token and move to a stablecoin-based subscription payment system. Bernhard already posted a good overview of the reasoning behind this decision but I’d like to add some background on how we used simulations to help us understand the dynamics of and issues with the token model. By way of disclaimer, I’m an advisor to MythX and co-creator of the Economy.

Introducing a dynamic bonding curve token model Utility tokens have received a lot of bad press recently, and for good reason. Many ICOs that sold utility tokens seem to have massively over-estimated the supply of tokens required for normal usage of their networks. The price of these tokens has been supported by speculative investors who presumably didn’t give much thought to the fact that they were not designed to function as a store of value and will likely be sold in return for usage as soon as they’re purchased by legitimate users, resulting in what is now commonly referred to as the velocity problem.

What if all our software licenses were compatible and we could go to a single integrated app store and sell say three days of Adobe Creative Cloud and buy two days of Microsoft Office? This flexibility would be a clear win for consumers but would surely lead to a loss of revenue for software vendors. Hmm, but what if this easy transferability of licenses also reduced piracy? In this post we present a simple proof of concept, representing software licenses as ERC721 tokens on the Ethereum blockchain, and using Metamask to passwordlessly log in to a web app by proving that you own the address that owns the tokens.

OpenSign is a free, decentralized alternative to products like DocuSign and EchoSign. It allows you to make agreements without requiring any trusted third party to keep track of your documents and signatures. td;dr The OpenSign dapp is currently an MVP, you can try it yourself now if you have some Ethereum and your browser has MetaMask installed. How does it work We’ve tried to make the process of creating multi-party agreements as simple as possible, but you will need some experience of using Ethereum and Metamask for any of this to make sense.

The Eyewitness platform is an open source messaging bot and management interface designed to let news organisations distribute stories and collects User Generated Content (UGC). The project is funded by Code for Africa and Bill and Melinda Gates Foundation. Feedback on our first release As detailed in the update for release 1, our first version of the Eyewitness chatbot focussed on providing a reason for people to connect with the bot.

The Eyewitness platform is an open source messaging bot and management interface designed to let news organisations distribute stories and collects User Generated Content (UGC). The project is funded by Code for Africa and Bill and Melinda Gates Foundation. Funding issues First off, an apology. When we pitched this project we intended to begin development sometime in spring and to have a working product out in the market by this point.

UPDATE: Out of 736 applications, it was announced today that we are one of the 22 winners to receive funding from #innovateAfrica. We’re absolutely thrilled to have been chosen, and we’re really excited about the potential for Eyewitness to transform newsgathering. What is EyeWitness Bot? Eyewitness will allow media organisations to leverage their community on Facebook to gather opinions, tip-offs and quotes. We will save journalists time, enabling them to collect information quickly and on a large scale, with an innovative AI bot and data analysis platform.

LastSeen is a simple chatbot that asks the user to check-in once a day and notifies their designated contact if they don’t. The project is a collaboration with Tom Hewitson. Tom’s father passed away last year. Once the initial shock had subsided he found himself often worrying about his mum now that she was on her own. As he was calling to check in on her every day he had the idea for LastSeen.