More on Productivity

Ellane W
3 years ago
The Last To-Do List Template I'll Ever Need, Years in the Making
The holy grail of plain text task management is finally within reach
Plain text task management? Are you serious?? Dedicated task managers exist for a reason, you know. Sheesh.
—Oh, I know. Believe me, I know! But hear me out.
I've managed projects and tasks in plain text for more than four years. Since reorganizing my to-do list, plain text task management is within reach.
Data completely yours? One billion percent. Beef it up with coding? Be my guest.
Enter: The List
The answer? A list. That’s it!
Write down tasks. Obsidian, Notenik, Drafts, or iA Writer are good plain text note-taking apps.
List too long? Of course, it is! A large list tells you what to do. Feel the itch and friction. Then fix it.
But I want to be able to distinguish between work and personal life! List two things.
However, I need to know what should be completed first. Put those items at the top.
However, some things keep coming up, and I need to be reminded of them! Put those in your calendar and make an alarm for them.
But since individual X hasn't completed task Y, I can't proceed with this. Create a Waiting section on your list by dividing it.
But I must know what I'm supposed to be doing right now! Read your list(s). Check your calendar. Think critically.
Before I begin a new one, I remind myself that "Listory Never Repeats."
There’s no such thing as too many lists if all are needed. There is such a thing as too many lists if you make them before they’re needed. Before they complain that their previous room was small or too crowded or needed a new light.
A list that feels too long has a voice; it’s telling you what to do next.
I use one Master List. It's a control panel that tells me what to focus on short-term. If something doesn't need semi-immediate attention, it goes on my Backlog list.
Todd Lewandowski's DWTS (Done, Waiting, Top 3, Soon) performance deserves praise. His DWTS to-do list structure has transformed my plain-text task management. I didn't realize it was upside down.
This is my take on it:
D = Done
Move finished items here. If they pile up, clear them out every week or month. I have a Done Archive folder.
W = Waiting
Things seething in the background, awaiting action. Stir them occasionally so they don't burn.
T = Top 3
Three priorities. Personal comes first, then work. There will always be a top 3 (no more than 5) in every category. Projects, not chores, usually.
S = Soon
This part is action-oriented. It's for anything you can accomplish to finish one of the Top 3. This collection includes thoughts and project lists. The sole requirement is that they should be short-term goals.
Some of you have probably concluded this isn't for you. Please read Todd's piece before throwing out the baby. Often. You shouldn't miss a newborn.
As much as Dancing With The Stars helps me recall this method, I may try switching their order. TSWD; Drilling Tunnel Seismic? Serenity After Task?
Master List Showcase
My Master List lives alone in its own file, but sometimes appears in other places. It's included in my Weekly List template. Here's a (soon-to-be-updated) demo vault of my Obsidian planning setup to download for free.
Here's the code behind my weekly screenshot:
## [[Master List - 2022|✓]] TO DO
![[Master List - 2022]]FYI, I use the Minimal Theme in Obsidian, with a few tweaks.
You may note I'm utilizing a checkmark as a link. For me, that's easier than locating the proper spot to click on the embed.
Blue headings for Done and Waiting are links. Done links to the Done Archive page and Waiting to a general waiting page.
Read my full article here.

Asher Umerie
3 years ago
What is Bionic Reading?
Senses help us navigate a complicated world. They shape our worldview - how we hear, smell, feel, and taste. People claim a sixth sense, an intuitive capacity that extends perception.
Our brain is a half-pool of grey and white matter that stores data from our senses. Brains provide us context, so zombies' obsession makes sense.
Bionic reading uses the brain's visual information and context to simplify text comprehension.
Stay with me.
What is Bionic Reading?
Bionic reading is a software application established by Swiss typographic designer Renato Casutt. The term honors the brain (bio) and technology's collaboration to better text comprehension.
The image above shows two similar paragraphs with bionic reading.
Notice anything yet?
This Twitter user did.
I did too...
Image text describes bionic reading-
New method to aid reading by using artificial fixation points. The reader focuses on the highlighted starting letters, and the brain completes the word.
How is Bionic Reading possible?
Do you remember seeing social media posts asking you to stare at a black dot for 30 seconds (or more)? You blink and see an after-image on your wall.
Our brains are skilled at identifying patterns and'seeing' familiar objects, therefore optical illusions are conceivable.
Brain and sight collaborate well. Text comprehension proves it.
Considering evolutionary patterns, humans' understanding skills may be cosmic luck.
Scientists don't know why people can read and write, but they do know what reading does to the brain.
One portion of your brain recognizes words, while another analyzes their meaning. Fixation, saccade, and linguistic transparency/opacity aid.
Let's explain some terms.
-
Fixation is how the eyes move when reading. It's where you look. If the eyes fixate less, a reader can read quicker. [Eye fixation is a physiological process](Eye fixation is a naturally occurring physiological process) impacted by the reader's vocabulary, vision span, and text familiarity.
-
Saccade - Pause and look around. That's a saccade. Rapid eye movements that alter the place of fixation, as reading text or looking around a room. They can happen willingly (when you choose) or instinctively, even when your eyes are fixed.
-
Linguistic transparency and opacity analyze how well a composite word or phrase may be deduced from its constituents.
The Bionic reading website compares these tools.
Text highlights lead the eye. Fixation, saccade, and opacity can transfer visual stimuli to text, changing typeface.
## Final Thoughts on Bionic Reading
I'm excited about how this could influence my long-term assimilation and productivity.
This technology is still in development, with prototypes working on only a few apps. Like any new tech, it will be criticized.
I'll be watching Bionic Reading closely. Comment on it!

wordsmithwriter
3 years ago
2023 Will Be the Year of Evernote and Craft Notetaking Apps.
Note-taking is a vital skill. But it's mostly learned.
Recently, innovative note-taking apps have flooded the market.
In the next few years, Evernote and Craft will be important digital note-taking companies.
Evernote is a 2008 note-taking program. It can capture ideas, track tasks, and organize information on numerous platforms.
It's one of the only note-taking app that lets users input text, audio, photos, and videos. It's great for collecting research notes, brainstorming, and remaining organized.
Craft is a popular note-taking app.
Craft is a more concentrated note-taking application than Evernote. It organizes notes into subjects, tags, and relationships, making it ideal for technical or research notes.
Craft's search engine makes it easy to find what you need.
Both Evernote and Craft are likely to be the major players in digital note-taking in the years to come.
Their concentration on gathering and organizing information lets users generate notes quickly and simply. Multimedia elements and a strong search engine make them the note-taking apps of the future.
Evernote and Craft are great note-taking tools for staying organized and tracking ideas and projects.
With their focus on acquiring and organizing information, they'll dominate digital note-taking in 2023.
Pros
Concentrate on gathering and compiling information
special features including a strong search engine and multimedia components
Possibility of subject, tag, and relationship structuring
enables users to incorporate multimedia elements
Excellent tool for maintaining organization, arranging research notes, and brainstorming
Cons
Software may be difficult for folks who are not tech-savvy to utilize.
Limited assistance for hardware running an outdated operating system
Subscriptions could be pricey.
Data loss risk because of security issues
Evernote and Craft both have downsides.
The risk of data loss as a result of security flaws and software defects comes first.
Additionally, their subscription fees could be high, and they might restrict support for hardware that isn't running the newest operating systems.
Finally, folks who need to be tech-savvy may find the software difficult.
Evernote versus. Productivity Titans Evernote will make Notion more useful. medium.com
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Farhad Malik
3 years ago
How This Python Script Makes Me Money Every Day
Starting a passive income stream with data science and programming
My website is fresh. But how do I monetize it?
Creating a passive-income website is difficult. Advertise first. But what useful are ads without traffic?
Let’s Generate Traffic And Put Our Programming Skills To Use
SEO boosts traffic (Search Engine Optimisation). Traffic generation is complex. Keywords matter more than text, URL, photos, etc.
My Python skills helped here. I wanted to find relevant, Google-trending keywords (tags) for my topic.
First The Code
I wrote the script below here.
import re
from string import punctuation
import nltk
from nltk import TreebankWordTokenizer, sent_tokenize
from nltk.corpus import stopwords
class KeywordsGenerator:
def __init__(self, pytrends):
self._pytrends = pytrends
def generate_tags(self, file_path, top_words=30):
file_text = self._get_file_contents(file_path)
clean_text = self._remove_noise(file_text)
top_words = self._get_top_words(clean_text, top_words)
suggestions = []
for top_word in top_words:
suggestions.extend(self.get_suggestions(top_word))
suggestions.extend(top_words)
tags = self._clean_tokens(suggestions)
return ",".join(list(set(tags)))
def _remove_noise(self, text):
#1. Convert Text To Lowercase and remove numbers
lower_case_text = str.lower(text)
just_text = re.sub(r'\d+', '', lower_case_text)
#2. Tokenise Paragraphs To words
list = sent_tokenize(just_text)
tokenizer = TreebankWordTokenizer()
tokens = tokenizer.tokenize(just_text)
#3. Clean text
clean = self._clean_tokens(tokens)
return clean
def _clean_tokens(self, tokens):
clean_words = [w for w in tokens if w not in punctuation]
stopwords_to_remove = stopwords.words('english')
clean = [w for w in clean_words if w not in stopwords_to_remove and not w.isnumeric()]
return clean
def get_suggestions(self, keyword):
print(f'Searching pytrends for {keyword}')
result = []
self._pytrends.build_payload([keyword], cat=0, timeframe='today 12-m')
data = self._pytrends.related_queries()[keyword]['top']
if data is None or data.values is None:
return result
result.extend([x[0] for x in data.values.tolist()][:2])
return result
def _get_file_contents(self, file_path):
return open(file_path, "r", encoding='utf-8',errors='ignore').read()
def _get_top_words(self, words, top):
counts = dict()
for word in words:
if word in counts:
counts[word] += 1
else:
counts[word] = 1
return list({k: v for k, v in sorted(counts.items(), key=lambda item: item[1])}.keys())[:top]
if __name__ == "1__main__":
from pytrends.request import TrendReq
nltk.download('punkt')
nltk.download('stopwords')
pytrends = TrendReq(hl='en-GB', tz=360)
tags = KeywordsGenerator(pytrends)\
.generate_tags('text_file.txt')
print(tags)Then The Dependencies
This script requires:
nltk==3.7
pytrends==4.8.0Analysis of the Script
I copy and paste my article into text file.txt, and the code returns the keywords as a comma-separated string.
To achieve this:
A class I made is called KeywordsGenerator.
This class has a function:
generate_tagsThe function
generate_tagsperforms the following tasks:
retrieves text file contents
uses NLP to clean the text by tokenizing sentences into words, removing punctuation, and other elements.
identifies the most frequent words that are relevant.
The
pytrendsAPI is then used to retrieve related phrases that are trending for each word from Google.finally adds a comma to the end of the word list.
4. I then use the keywords and paste them into the SEO area of my website.
These terms are trending on Google and relevant to my topic. My site's rankings and traffic have improved since I added new keywords. This little script puts our knowledge to work. I shared the script in case anyone faces similar issues.
I hope it helps readers sell their work.

Techletters
2 years ago
Using Synthesia, DALL-E 2, and Chat GPT-3, create AI news videos
Combining AIs creates realistic AI News Videos.
Powerful AI tools like Chat GPT-3 are trending. Have you combined AIs?
The 1-minute fake news video below is startlingly realistic. Artificial Intelligence developed NASA's Mars exploration breakthrough video (AI). However, integrating the aforementioned AIs generated it.
AI-generated text for the Chat GPT-3 based on a succinct tagline
DALL-E-2 AI generates an image from a brief slogan.
Artificial intelligence-generated avatar and speech
This article shows how to use and mix the three AIs to make a realistic news video. First, watch the video (1 minute).
Talk GPT-3
Chat GPT-3 is an OpenAI NLP model. It can auto-complete text and produce conversational responses.
Try it at the playground. The AI will write a comprehensive text from a brief tagline. Let's see what the AI generates with "Breakthrough in Mars Project" as the headline.
Amazing. Our tagline matches our complete and realistic text. Fake news can start here.
DALL-E-2
OpenAI's huge transformer-based language model DALL-E-2. Its GPT-3 basis is geared for image generation. It can generate high-quality photos from a brief phrase and create artwork and images of non-existent objects.
DALL-E-2 can create a news video background. We'll use "Breakthrough in Mars project" again. Our AI creates four striking visuals. Last.
Synthesia
Synthesia lets you quickly produce videos with AI avatars and synthetic vocals.
Avatars are first. Rosie it is.
Upload and select DALL-backdrop. E-2's
Copy the Chat GPT-3 content and choose a synthetic voice.
Voice: English (US) Professional.
Finally, we generate and watch or download our video.
Synthesia AI completes the AI video.
Overview & Resources
We used three AIs to make surprisingly realistic NASA Mars breakthrough fake news in this post. Synthesia generates an avatar and a synthetic voice, therefore it may be four AIs.
These AIs created our fake news.
AI-generated text for the Chat GPT-3 based on a succinct tagline
DALL-E-2 AI generates an image from a brief slogan.
Artificial intelligence-generated avatar and speech

Khoi Ho
3 years ago
After working at seven startups, here are the early-stage characteristics that contributed to profitability, unicorn status or successful acquisition.
I've worked in a People role at seven early-stage firms for over 15 years (I enjoy chasing a dream!). Few of the seven achieved profitability, including unicorn status or acquisition.
Did early-stage startups share anything? Was there a difference between winners and losers? YES.
I support founders and entrepreneurs building financially sustainable enterprises with a compelling cause. This isn't something everyone would do. A company's success demands more than guts. Founders drive startup success.
Six Qualities of Successful Startups
Successful startup founders either innately grasped the correlation between strong team engagement and a well-executed business model, or they knew how to ask and listen to others (executive coaches, other company leaders, the team itself) to learn about it.
Successful startups:
1. Co-founders agreed and got along personally.
Multi-founder startups are common. When co-founders agree on strategic decisions and are buddies, there's less friction and politics at work.
As a co-founder, ask your team if you're aligned. They'll explain.
I've seen C-level leaders harbor personal resentments over disagreements. A co-departure founder's caused volatile leadership and work disruptions that the team struggled to manage during and after.
2. Team stayed.
Successful startups have low turnover. Nobody is leaving. There may be a termination for performance, but other team members will have observed the issues and agreed with the decision.
You don't want organizational turnover of 30%+, with leaders citing performance issues but the team not believing them. This breeds suspicion.
Something is wrong if many employees leave voluntarily or involuntarily. You may hear about lack of empowerment, support, or toxic leadership in exit interviews and from the existing team. Intellectual capital loss and resource instability harm success.
3. Team momentum.
A successful startup's team is excited about its progress. Consistently achieving goals and having trackable performance metrics. Some describe this period of productivity as magical, with great talents joining the team and the right people in the right places. Increasing momentum.
I've also seen short-sighted decisions where only some departments, like sales and engineering, had goals. Lack of a unified goals system created silos and miscommunication. Some employees felt apathetic because they didn't know how they contributed to team goals.
4. Employees advanced in their careers.
Even if you haven't created career pathing or professional development programs, early-stage employees will grow and move into next-level roles. If you hire more experienced talent and leaders, expect them to mentor existing team members. Growing companies need good performers.
New talent shouldn't replace and discard existing talent. This creates animosity and makes existing employees feel unappreciated for their early contributions to the company.
5. The company lived its values.
Culture and identity are built on lived values. A company's values affect hiring, performance management, rewards, and other processes. Identify, practice, and believe in company values. Starting with team values instead of management or consultants helps achieve this. When a company's words and actions match, it builds trust.
When company values are beautifully displayed on a wall but few employees understand them, the opposite is true. If an employee can't name the company values, they're useless.
6. Communication was clear.
When necessary information is shared with the team, they feel included, trusted, and like owners. Transparency means employees have the needed information to do their jobs. Disclosure builds trust. The founders answer employees' questions honestly.
Information accessibility decreases office politics. Without transparency, even basic information is guarded and many decisions are made in secret. I've seen founders who don't share financial, board meeting, or compensation and equity information. The founders' lack of trust in the team wasn't surprising, so it was reciprocated.
The Choices
Finally. All six of the above traits (leadership alignment, minimal turnover, momentum, professional advancement, values, and transparency) were high in the profitable startups I've worked at, including unicorn status or acquisition.
I've seen these as the most common and constant signals of startup success or failure.
These characteristics are the product of founders' choices. These decisions lead to increased team engagement and business execution.
Here's something to consider for startup employees and want-to-bes. 90% of startups fail, despite the allure of building something new and gaining ownership. With the emotional and time investment in startup formation, look for startups with these traits to reduce your risk.
Both you and the startup will thrive in these workplaces.
