Symbyte

Would you know if a video in your feed had been made by AI? The EU AI Act, enforceable since 2 August, now expects certain AI-generated content, including deepfakes, to be clearly labelled. That's one of four stories in this edition of the AI Recap, alongside IBM and OpenAI bringing their models to enterprise, and new releases from Google and NVIDIA. #symbyte #airecap

A whole Java project moved from 1.8 to Java 21 in about an hour, using an agent. It had been waiting on that upgrade for five years. In this clip from the podcast, the conversation turns to what that means for how most of us will end up working with agents. Link to the full episode in the comments. #ai #aiagents #java #softwaredevelopment #symbyte

There's a theory that pizza orders near the Pentagon spike right before major military decisions. Whether or not you buy it, it's a good example of how ordinary data can hint at things nobody meant to reveal, the same logic behind Strava accidentally exposing secret military bases through soldiers' running routes. Episode 3 of Two Guys in a Random Forest digs into stories like these: prediction markets, autonomous drones, and how AI agents are already reshaping the way people work day to day. (Link in the comments) #symbyte #datascience #podcast

Rand Merchant Bank had two IFRS 9 credit models still running in Excel, both taking over eight hours to calculate. Excel had done the job for years, but at that scale it was becoming a liability rather than a tool: slow to run, hard to audit, and reliant on whoever built the spreadsheet in the first place. We ported both models to Python, running on-prem. Calculation time dropped from over eight hours to under ten minutes. The deployment process was automated too, with a CLI tool handling IFRS 9 trade classifications, so there's less room for manual error creeping in. On top of that, we built in proper monitoring and observability, so the team isn't just faster; they can actually see what the system is doing and trust the output. The result: 700+ man hours saved annually, and models that are fast, stable, and genuinely auditable. If your credit models are still living in spreadsheets and starting to strain under their own weight, that's a conversation worth having. Get in touch, link in the comments.

Most businesses use their data to explain what already happened. Fewer use it to build something new. That's the shift with data products: instead of another report on last quarter, it's a new feature inside your existing product, or an entirely new offering built off patterns your data already holds. It's the same thinking behind the trend-spotting tool we built for Shoprite, an automated system that surfaces emerging consumer behaviour straight from their own data, rather than another dashboard someone has to interpret. Symbyte works with clients to map out what's possible with what they already have, then build it. Worth asking: is your data only being reported on, or is it being built with? #symbyte #datamonetisation #data #aidata

Look, ten years ago there was no such thing as a "data scientist" degree. You just did computer science, got good enough at maths, and somewhere along the way someone started calling you a quant. Same skillset, new job title. Now you can walk into a university on day one and study to become a data scientist. Ten years to go from "that's just computer science" to its own discipline. Computer science has been doing data science since at least the '60s, it just didn't have the name yet. #symbyte #datascience

Every time humanity invents a new way to store information outside our heads, something in the theory says a piece of our thinking dies with it. Socrates argued this about writing. Critics said the same about the printing press. Our newest blog post asks the obvious next question: what happens when we outsource not just memory, but thinking itself, to an LLM? There's a fascinating bit of neuroscience in there too, the kind of evidence that makes the "we're becoming lazier" argument harder to dismiss than you'd think. The real question isn't whether AI makes us smarter or dumber. It's whether we're building a bicycle for the mind, or a mobility scooter for it. [Blog link in first comment]

A lot of businesses hesitate to bring in a data or AI partner because the process feels like a black box. Here's what working with Symbyte actually looks like. It starts with understanding the problem, not the technology. We sit down with your team, figure out where the real bottlenecks are, and only then start talking about what to build. From there, we scope something specific and achievable, not a sprawling multi year roadmap that never ships. Development happens in stages, with your team seeing progress along the way rather than waiting months for a reveal. Once something is live, we don't disappear. Support and iteration are part of the relationship, because the first version is rarely the last version. If you've been putting off a data or AI project because you weren't sure what working with a consultancy actually involves, this is roughly it. #symbyte #dataconsulting

"There is still no AI." Bold thing for a data and AI consultancy to say. Our latest article drops the mysticism and treats AI as an engineering challenge instead: guardrails, retrieval, error correction, a human always checking the output. We use Meta's own internal analytics agent as the example, and it's the same lens we apply to every agent we build at Symbyte. #ai #symbyte #meta #dataanalytics

"Privacy is dead." That's not us saying it, it's a line from this week's podcast clip. The bit that got us was the follow up: who actually gets to decide when data collection crosses an ethical line, once photos and data from a decade ago are already out there for anyone who wants to find them. [Podcast link in first comment]