Exclusive AI Cheat Sheet: Artificial Intelligence Beyond GenAI

In this newsletter:

• 📑 The only AI report tailored for tech professionals

• 🔥 AI Hot topics: AI pursues human-like reasoning, plus how the new presidency might change AI regulations

• 🐍 Using Python to build amazing AI apps

Tired of generic AI reports?

We feel you. Many AI whitepapers just skim the surface — or worse, peddle promotional content instead of useful information.  

That’s why we set out to do something different. We just released a no-fluff, super practical handbook that has everything you need to get a firm grip on AI’s current technical ecosystem.

Check it out here: AI Beyond GenAI: State of Tech Research in 2024

 What’s inside?

• In-depth AI tech analysis - Get a rundown of the most powerful AI and ML tools today, including languages, libraries, frameworks, databases, MLOps services, and ready-to-use GenAI solutions. 

• Cost insights - See pricing models for different AI services so you can budget your project. 

• Targeted guidance - Find technical and market knowledge relevant to your role, whether you're in tech leadership, product development, engineering, or business expansion. 

• Technical use cases - See how you can use AI to improve your offerings and operations.

• Quick takeaways - Get the gist from easy-to-digest section summaries even if you only have five minutes.

Why should you care about AI?

The $15.7-trillion AI revolution is well and truly here. Anyone in tech needs a solid grasp of the key tools driving its growth, how much they cost, and which ones to pick for their projects. 

That’s why our whitepaper answers practical questions like:

What tools do engineers and data scientists use to develop today’s AI models? We list and discuss the technologies integral to today’s AI projects:

• Primary language and core libraries: Python, Pandas, Scikit-learn, Matplotlib, Streamlit

• Deep learning frameworks: TensorFlow, PyTorch, JAX, Keras

• Vector databases: ChromaDB, FAISS, Pinecone

How is AI used in the real world right now? See AI in action! Understand how it’s used in NLP, STT, content generation, recommendation systems, and predictive analytics to get ideas for your projects.

How much do AI tools and services cost? Understand how different AI pricing models work. We dive deep into resource-based, compute unit, and generative model cost structures.  

Your ultimate AI toolkit

Designed to be useful for anyone interested in AI — from curious newcomers to experienced developers — this guide fills you in on everything you need to know to launch your AI initiative.

Download the full report to learn more!

Hot Topics

Here’s a little round-up of the latest AI-related news.

🧑‍💻 Anthropic's AI gets smarter, more human-like

Hot on the heels of an enhanced Claude 3.5 Sonnet and a new model called Claude 3.5 Haiku, AI research firm Anthropic launched a new experimental tool: computer use, now public beta. It allows developers to create AI systems that can look at a screen, move a cursor, click buttons, and type text — in other words, interact with computers as humans do. It’s still error-prone at this stage, but that’s not stopping early adopters like Canva and DoorDash from trying it out.

🧠 Brainier than ever: OpenAI wants to think like a human  

As traditional large language models hit a wall, OpenAI and its rivals are racing to develop smarter AI. They're exploring test-time computing — a technique that allows AI to evaluate multiple answers in real time to mimic more human-like reasoning. Could this radically change AI hardware demands and challenge Nvidia’s chip dominance?

💰 AI tries to make banking safer

SymphonyAI wants to democratize risk detection models and make it cheaper for banks to fight financial crime. The solution? Combine transfer learning and SaaS. Transfer learning is an ML technique that lets AI models apply insights from one task to enhance performance on related ones so banks can improve risk management without spending a ton on data. Combined with a pay-as-you-go SaaS model, this should allow even smaller financial institutions to spot risks faster and stop financial criminals in their tracks. 

❓Will Trump deregulate AI?

Intent on scrapping the current AI policy framework, the president-elect wants to minimize regulatory interference — a move that could dismantle established safety protocols and development guidelines. Republicans have long criticized the NIST for promoting what they view as “woke” AI safety standards influenced by liberal agendas. Early in his campaign, Trump also promised to ban AI use for censoring speech. 

🚗 What Trump’s second term could mean for AI, crypto, and EV

As Trump retakes the White House, analysts expect a more laissez-faire approach to tech AI regulations. The incoming president’s hands-off approach to crypto could potentially fuel a Bitcoin boom. And while the fate of EV incentives still hangs by a thread, Trump’s coziness with Elon Musk might be a silver lining for Tesla. The bottom line? Buckle up — it's going to be a wild ride.

🍏 Apple puts AI in everyday tech

Apple's latest iOS 18.2 public beta gives everyday users access to previously developer-exclusive tools: Genmoji and Image Playground. Siri now uses ChatGPT to make interactions more intuitive, and Visual Intelligence allows iPhone 16 users to identify objects and translate text directly through the camera.

You have to join a waitlist to access Genmoji, Image Wand, and Image Playground. Still, people who were previously part of the developer beta can access Writing Tools, ChatGPT, and Visual Intelligence right away.

Apple also released the macOS 15.2 public beta. It has many of iOS 18.2's features except Visual Intelligence and Genmoji, which are currently exclusive to iPhones and iPads.

🏅 OpenAI leads the gold rush

OpenAI's valuation hit a staggering $157 billion after a fresh $6.6 billion funding raise, doubling its value from just months prior. As the investment frenzy continues, companies like Perplexity and Anthropic are also seeing their market caps skyrocket. Elon Musk's xAI, in particular, is eyeing a colossal $45 billion valuation with its new funding round, making it one of the biggest VC-backed startups today. 

🐍 Python drives global developer surge

Far from making developers obsolete, AI is actually encouraging more people to build AI models, according to this year’s Octoverse report. Python also eclipsed JavaScript as GitHub's top language, signaling widespread enthusiasm for data science and machine learning. The report even shows a 59% jump in generative AI project contributions, with a notable spike from developers in India and Brazil.

Speaking of Python… 

We recently flexed our technical muscles on a project with Swirl — a Python-based AI platform that can generate ChatGPT-like insights from internal enterprise data and external sources.

In a nutshell, Swirl pulls vast amounts of information from various public and private sources such as Google, Google News, Microsoft OneDrive, and email systems. It then combines LLM’s power and RAG’s precision to clean complex data sets and extract insights. This allows businesses to make sense of previously siloed info spread across various departments and systems to tap into real-time decision-making insights.

All this heavy lifting usually requires more resource-intensive languages. But even though Python isn’t known for its raw speed, it worked well for building Swirl — especially when we combined it with Django, Celery, and Postgres!

The dedicated team we assigned to this project managed to build a high-performance app with lots of integrations and features, showing just how well Python can deal with complex projects and how fast it can be to develop with it. 

Want to learn more about what we’ve been up to? Head to our website, where you can learn more about our recent projects.

Looking for a team that can make the most of Python's versatility to build high-performance AI apps? Let’s chat! We’d love to help bring your ideas to life!