Speed reading is a simple tweak to read faster without losing comprehension. Most people read uselessly because they were never know that how to process words faster. Traditional reading habits, such as sub vocalization and linear reading, slow you down radically.
The Hack: Chunking Words Instead of Reading Word by Word
Instead of reading one word at a time, train your eyes to process groups of words (chunks) in a single glance. This technique eliminates unnecessary pauses and increases comprehension.

How to Use Chunking for Instant Speed Reading
1. Widen Your Peripheral Vision
Instead of focusing on single words, expand your gaze to capture 3–5 words at a time.
This reduces the number of eye movements per line and speeds up reading.
2. Eliminate Sub vocalization
Most people “hear” words in their heads while reading, which slows them down.
To break this habit, use your finger or a pen to guide your eyes faster than you can “speak” the words.
3. Use a Pacer (Finger or Pen)
Move your finger under the text at a steady pace, forcing your eyes to keep up.
This minimizes backtracking and increases reading speed without losing comprehension.
4. Preview Before You Read
Skim the headings, bold text, and first sentences before diving into the details.
This primes your brain for what’s coming and improves understanding.
Who Benefits from This Hack?
Students Preparing for Exams: Cover more material in less time.
Professionals & Researchers: Process large volumes of text efficiently.
Avid Readers: Enjoy books faster without missing key details.

Final Thoughts: Read Faster, Learn More
Slow reading isn’t a skill issue it’s a habit issue. By applying the chunking method, reducing sub vocalization, and using a pacer, you can instantly double your reading speed while improving comprehension.

I am an accomplished Data Analyst and Data Scientist with over a decade of experience in data analysis, software engineering, natural language processing, and machine learning. I have successfully led teams in developing large-scale computer vision platforms, created web crawlers capable of managing petabytes of data, and co-invented a patented NLP methodology. My strong foundation in competitive programming and five years of teaching computer science and artificial intelligence courses have equipped me with expertise in algorithm development, data consistency strategies, and AI-driven automation. Proficient in Python, Java, machine learning frameworks, and cloud technologies, I am dedicated to driving AI innovation and delivering data-centric solutions. I am based in North Carolina, USA.