AI-Driven Semantic Search

Scholar Labs uses AI to analyze full-text documents, not just citation counts, to surface papers that are contextually relevant.

No Citation or Impact-Factor Filters

Unlike Google Scholar, Scholar Labs does not let users filter results by citation count or journal impact factor, because Google argues these metrics can be misleading.

Prioritizes Recency and Authorship

The tool factors in who wrote the paper, where it was published, and how recently, rather than just how many times it's been cited.

Explainable Results

Scholar Labs doesn’t just list results - it explains why a paper is relevant by showing how it relates to your query.

Controlled Rollout and Criticism

The feature is in limited testing with logged-in users. Some researchers worry that replacing traditional metrics with AI judgment could risk quality and rigor.

Promise vs Reality

The pen is marketed as a tool to cheat on paper exams by scanning printed text and using AI to give instant answers.

Poor Accuracy

In tests, the device often misreads scanned text or produces nonsensical, incorrect answers. 

Language Barrier

The pen’s menu is in Chinese, which made it difficult for the reviewer to even use the correct “Q&A” mode.

Clunky and Obvious

The physical design is too large and conspicuous - not discreet enough to use during a test without drawing attention. 

Better Uses Than Cheating

While it fails at cheating, the pen has some value as a translation device (handling multiple languages). Students say simpler methods like using a phone + ChatGPT are more effective for cheating.

Start With a Clear Visual Goal

Before typing anything, decide what you’re aiming for product photo, a thumbnail, a portrait, an infographic, or a background. When the goal is clear, your prompts become sharper and the output instantly improves.

Describe the Scene With Real-World Details

AI responds better to specifics than vague ideas. Mention lighting (soft studio, natural daylight), camera angles (close-up, wide shot), textures, colors, and mood. The more concrete the details, the more realistic the image feels.

Use High-Quality Style Cues

If you want a polished look, reference styles tied to real photography or design: studio lighting, 35mm lens, minimalist layout, editorial style, or flat-lay composition. These anchor the AI to professional aesthetics.

Refine With Negative Prompts

This is where images go from “good” to “clean.” Tell the AI what to avoid: blurry edges, distorted hands, extra limbs, low resolution, weird reflections, and text artifacts. It sharpens the final output dramatically.

Iterate and Adjust Like a Designer

Treat each generation like a draft. Change one variable at a time, lighting, pose, angle, color palette, until the image feels right. Professionals iterate, not fire-and-forget.

Followr – Twitter Growth Tool

Followr helps creators and brands grow on Twitter without spending hours posting manually. It studies your niche, schedules content, and engages with the right audience so your profile grows consistently. The tool feels more like a smart social assistant that knows what works on the platform. It’s handy for anyone trying to build a steady presence without burning time.

CoolAIID – AI Interior Design Platform

CoolAIID turns interior design ideas into realistic renders in seconds. You can upload a room photo, pick a style, and the tool reimagines the entire space with clean layouts and vivid visuals. It’s a great way to explore concepts before spending on furniture or décor. Designers, homeowners, and real estate folks get the most out of it.

Akasa – AI-Driven Healthcare RCM

Akasa uses AI to clean up the messy backend of healthcare revenue cycles. It automates billing, claims, and financial workflows so hospitals get paid faster with fewer errors. What makes it stand out is the blend of automation with human-in-the-loop oversight. It brings order to a part of healthcare that usually feels chaotic.

Braze – AI Marketing Automation

Braze helps brands send smarter messages across email, app, and web. Its AI predicts the right moment to reach each user and adjusts content based on behavior. The result is marketing that feels personal instead of spammy. It’s built for growth teams that want better engagement without juggling a dozen tools.

HR Marga

HR Marga focuses on using AI to simplify hiring and HR workflows. It screens candidates, highlights skills, and cuts down on repetitive tasks that slow talent teams down. The goal is to help companies recruit faster and with more clarity. It’s a solid pick for growing teams that need smarter HR tools.

MockAI

MockAI creates realistic AI-driven interview practice environments. Users can rehearse answers, get feedback, and understand what skills they need to improve. It’s especially helpful for job seekers preparing for technical or behavioral interviews. Think of it as a personal career coach that doesn’t judge.

Overjoy

Overjoy builds tools that help companies understand how their employees actually feel. The platform analyzes feedback, conversations, and engagement signals to show what’s working and what’s broken in workplace culture. It gives leaders a way to fix issues early rather than waiting for surveys. It’s people analytics done right.

Juztina

Juztina uses AI to automate customer-facing tasks like replies, onboarding messages, and support conversations. It adapts to a company’s tone and learns from real interactions, so responses stay natural. Businesses use it to scale communication without losing quality. It’s a neat blend of automation and brand personality.