Hot off the Wires 🔥

We're eavesdropping on the smartest minds in research. 🤫 Don't miss out on what they're cooking up! In this section, we dissect some of the juiciest tech research that holds the key to what's next in tech.⚡

Remember the last time you had to create an academic poster? Hours spent wrestling with PowerPoint, trying to squeeze a 20-page research paper onto a single page without making it look like a chaotic mess. You're juggling text blocks, fighting with image placements, and constantly asking yourself: "Does this even make sense to someone who hasn't read my paper?"

Well, researchers from the University of Waterloo, NUS & Oxford have collaborated & cracked this age-old academic puzzle with Paper2Poster — the first AI system that can automatically transform dense scientific papers into polished, presentation-ready posters. Think of it as having a brilliant design assistant who's read thousands of research papers and knows exactly how to distil complex ideas into visually compelling layouts.

So, what’s new?

Academic poster creation has always been the Achilles' heel of scientific communication — it's like trying to fit a novel onto a movie poster while keeping all the important plot points intact.

Traditional AI approaches have failed because:

• No Visual Feedback: They're essentially designing blindfolded

• Poor Spatial Reasoning: Great at understanding content, terrible at layout

• Layout Disasters: Text overflows, misaligned images, ransom note aesthetics

Paper2Poster changes the game by introducing both an automated generation system AND the first benchmark to measure if these AI posters actually work.

Under the hood…

The magic happens through something called PosterAgent - a multi-agent AI system that works like a team of specialists, each handling a different aspect of poster creation. Instead of trying to do everything at once, it breaks down the complex task into manageable steps, much like how a professional design team would approach the project.

The system consists of three key players working in harmony:

• The Parser acts like a super-efficient research assistant. It reads through your entire paper (even those 50-page monsters) and creates what researchers call an "asset library." Think of it as intelligently extracting all the good stuff: key findings from each section, important figures, crucial tables, and compelling data visualisations. It utilises Marker & Docling to convert your PDF into structured Markdown, then utilises AI to organise everything into a neat, searchable digital library.

• The Planner is the strategic architect of the operation

  1. It starts by pairing each visual (like graphs or figures) with the right text, kind of like matching socks after laundry, but way smarter. It uses an LLM to figure out which descriptions best go with which visuals, ensuring every panel tells a complete story.

  2. Once it has all the important pieces, it figures out how to arrange them on the poster. Rather than randomly placing elements, it uses a clever "binary-tree layout" strategy, i.e., essentially creating a hierarchical map that ensures everything fits perfectly while maintaining logical reading flow. Imagine fitting furniture into a tiny studio apartment — it maps out where each block of content should go so that the flow feels natural and nothing looks crammed.

  3. Finally, the Planner rewrites the content into clean, crisp bullet points for each section, trimming the fluff and packing only what’s essential. Think of it as the poster’s Marie Kondo moment. These refined summaries are then handed off to the Painter-Commenter loop for visual polish.

• The Painter-Commenter Loop is where the real innovation happens. This is essentially an AI artist working with an AI critic in real-time. The Painter creates actual visual elements using code (specifically the python-pptx library), generating draft sections of the poster. But here's the brilliant part: the Commenter (a vision-language model) actually looks at what was created and provides feedback like "too much text here," "this section looks great," or "the layout is unbalanced."

They go back and forth, iteratively refining each panel until it's perfect. It's like having a design review meeting happening automatically inside the AI system, ensuring nothing gets published until it meets professional standards.

What’s the intrigue?

To evaluate how well these AI-generated posters actually work, the researchers created something called "PaperQuiz" - a clever metric that tests whether someone looking at just the poster can understand the core ideas from the original paper. They generate questions from the research paper and see how well AI readers can answer them using only the poster. It's essentially testing whether the poster succeeds in its fundamental job: communicating research effectively.

Results speak louder than words…

The performance metrics? Impressive — and refreshingly practical.

Across fields like CS, biology, and more, PosterAgent consistently delivers accurate, structured, and readable posters, regardless of domain complexity.

Why does this matter?

We're looking at a potential game-changer for scientific communication. Academic conferences are the lifeblood of research progress, and poster sessions are where much of the real networking and idea exchange happens. But creating effective posters has always been a significant barrier, especially for early-career researchers who may lack design skills or resources.

However, we feel that this research isn’t just about making pretty posters — it’s a glimpse into the future of how AI will supercharge professional communication.

• For Researchers & PhD Students:

  • Save hours on poster prep before conferences

  • Improve the clarity and impact of your work

  • Level the playing field — even without design skills

• For Data Scientists:

  • Summarise internal reports, whitepapers, or model documentation into crisp visual briefs

  • Build interactive dashboards that communicate insights, not just numbers

• For Startup Founders & PMs:

  • Repurpose technical documentation into investor-ready or sales-facing visuals

  • Use similar workflows to turn dense research into engaging product one-pagers or explainer decks

This also hints at a broader design pattern — "AI as collaborative creator" — where specialised agents work like expert teams, giving structured feedback, aligning vision and execution, and iterating toward quality.

In short, this isn't just a poster tool — it's a blueprint for how AI can co-create in complex, domain-specific tasks.

10x Your Workflow with AI 📈

Work smarter, not harder! In this section, you’ll find prompt templates 📜 & bleeding-edge AI tools ⚙️ to free up your time.

Fresh Prompt Alert!🚨

Stuck in a swirl of “Is this idea any good?” Spark and Trouble have your back!

This week’s prompt helps you pressure-test any business idea with Starbursting — a sharp, structured way to spot blind spots, bust assumptions, and surface golden insights.

Time to think deeper, move faster, and outsmart the chaos.

3 AI Tools You JUST Can't Miss 🤩

• 🌄 MorningCommute: Listen to, respond to, and manage your emails hands-free while driving.

• 📃 Spine AI: Generate and refine deep research reports from thousands of sources

• 🤖 ShumerPrompts: Discover AI Prompts for better results

Spark 'n' Trouble Shenanigans 😜

Remember when we tore down GeneratedAssets a couple of weeks ago, and Spark couldn't stop ranting about how it only worked for US markets? "What about us poor Indian investors?" she whined dramatically, clutching her Diet Coke.

Well, turns out Trouble actually listened for once!

Instead of binge-watching Amazon Prime last weekend, our puzzle-piece Dev decided to channel his inner chaos into something productive. Armed with GitHub Copilot Agent, Trouble went full mad-scientist mode and birthed "IndiQuant AI" – basically GenerateAssets' desi cousin who speaks fluent NSE and benchmarks against Nifty50 instead of S&P 500.

The best part? You can literally create investment themes as quirky as "companies that spam ads during IPL cricket matches" and watch it transform into an actual, tradeable index.

The MVP is looking chef's kiss. Check it out for yourself 👇

Spark's already plotting themes like "startups that raised funding during Diwali" and "companies whose CEOs tweet too much." The possibilities are endless, and slightly terrifying.

And if this sounds like something you’d totally geek out over (because hey, if your vibe can be a playlist, it can be a portfolio too), let us know here 👇