More on Technology

VIP Graphics
3 years ago
Leaked pitch deck for Metas' new influencer-focused live-streaming service
As part of Meta's endeavor to establish an interactive live-streaming platform, the company is testing with influencers.
The NPE (new product experimentation team) has been testing Super since late 2020.
Bloomberg defined Super as a Cameo-inspired FaceTime-like gadget in 2020. The tool has evolved into a Twitch-like live streaming application.
Less than 100 creators have utilized Super: Creators can request access on Meta's website. Super isn't an Instagram, Facebook, or Meta extension.
“It’s a standalone project,” the spokesperson said about Super. “Right now, it’s web only. They have been testing it very quietly for about two years. The end goal [of NPE projects] is ultimately creating the next standalone project that could be part of the Meta family of products.” The spokesperson said the outreach this week was part of a drive to get more creators to test Super.
A 2021 pitch deck from Super reveals the inner workings of Meta.
The deck gathered feedback on possible sponsorship models, with mockups of brand deals & features. Meta reportedly paid creators $200 to $3,000 to test Super for 30 minutes.
Meta's pitch deck for Super live streaming was leaked.
What were the slides in the pitch deck for Metas Super?
Embed not supported: see full deck & article here →
View examples of Meta's pitch deck for Super:
Product Slides, first
The pitch deck begins with Super's mission:
Super is a Facebook-incubated platform which helps content creators connect with their fans digitally, and for super fans to meet and support their favorite creators. In the spirit of Late Night talk shows, we feature creators (“Superstars”), who are guests at a live, hosted conversation moderated by a Host.
This slide (and most of the deck) is text-heavy, with few icons, bullets, and illustrations to break up the content. Super's online app status (which requires no download or installation) might be used as a callout (rather than paragraph-form).
Meta's Super platform focuses on brand sponsorships and native placements, as shown in the slide above.
One of our theses is the idea that creators should benefit monetarily from their Super experiences, and we believe that offering a menu of different monetization strategies will enable the right experience for each creator. Our current focus is exploring sponsorship opportunities for creators, to better understand what types of sponsor placements will facilitate the best experience for all Super customers (viewers, creators, and advertisers).
Colorful mockups help bring Metas vision for Super to life.
2. Slide Features
Super's pitch deck focuses on the platform's features. The deck covers pre-show, pre-roll, and post-event for a Sponsored Experience.
Pre-show: active 30 minutes before the show's start
Pre-roll: Play a 15-minute commercial for the sponsor before the event (auto-plays once)
Meet and Greet: This event can have a branding, such as Meet & Greet presented by [Snickers]
Super Selfies: Makers and followers get a digital souvenir to post on social media.
Post-Event: Possibility to draw viewers' attention to sponsored content/links during the after-show
Almost every screen displays the Sponsor logo, link, and/or branded background. Viewers can watch sponsor video while waiting for the event to start.
Slide 3: Business Model
Meta's presentation for Super is incomplete without numbers. Super's first slide outlines the creator, sponsor, and Super's obligations. Super does not charge creators any fees or commissions on sponsorship earnings.
How to make a great pitch deck
We hope you can use the Super pitch deck to improve your business. Bestpitchdeck.com/super-meta is a bookmarkable link.
You can also use one of our expert-designed templates to generate a pitch deck.
Our team has helped close $100M+ in agreements and funding for premier companies and VC firms. Use our presentation templates, one-pagers, or financial models to launch your pitch.
Every pitch must be audience-specific. Our team has prepared pitch decks for various sectors and fundraising phases.
Pitch Deck Software VIP.graphics produced a popular SaaS & Software Pitch Deck based on decks that closed millions in transactions & investments for orgs of all sizes, from high-growth startups to Fortune 100 enterprises. This easy-to-customize PowerPoint template includes ready-made features and key slides for your software firm.
Accelerator Pitch Deck The Accelerator Pitch Deck template is for early-stage founders seeking funding from pitch contests, accelerators, incubators, angels, or VC companies. Winning a pitch contest or getting into a top accelerator demands a strategic investor pitch.
Pitch Deck Template Series Startup and founder pitch deck template: Workable, smart slides. This pitch deck template is for companies, entrepreneurs, and founders raising seed or Series A finance.
M&A Pitch Deck Perfect Pitch Deck is a template for later-stage enterprises engaging more sophisticated conversations like M&A, late-stage investment (Series C+), or partnerships & funding. Our team prepared this presentation to help creators confidently pitch to investment banks, PE firms, and hedge funds (and vice versa).
Browse our growing variety of industry-specific pitch decks.

Shalitha Suranga
3 years ago
The Top 5 Mathematical Concepts Every Programmer Needs to Know
Using math to write efficient code in any language
Programmers design, build, test, and maintain software. Employ cases and personal preferences determine the programming languages we use throughout development. Mobile app developers use JavaScript or Dart. Some programmers design performance-first software in C/C++.
A generic source code includes language-specific grammar, pre-implemented function calls, mathematical operators, and control statements. Some mathematical principles assist us enhance our programming and problem-solving skills.
We all use basic mathematical concepts like formulas and relational operators (aka comparison operators) in programming in our daily lives. Beyond these mathematical syntaxes, we'll see discrete math topics. This narrative explains key math topics programmers must know. Master these ideas to produce clean and efficient software code.
Expressions in mathematics and built-in mathematical functions
A source code can only contain a mathematical algorithm or prebuilt API functions. We develop source code between these two ends. If you create code to fetch JSON data from a RESTful service, you'll invoke an HTTP client and won't conduct any math. If you write a function to compute the circle's area, you conduct the math there.
When your source code gets more mathematical, you'll need to use mathematical functions. Every programming language has a math module and syntactical operators. Good programmers always consider code readability, so we should learn to write readable mathematical expressions.
Linux utilizes clear math expressions.
Inbuilt max and min functions can minimize verbose if statements.
How can we compute the number of pages needed to display known data? In such instances, the ceil function is often utilized.
import math as m
results = 102
items_per_page = 10
pages = m.ceil(results / items_per_page)
print(pages)Learn to write clear, concise math expressions.
Combinatorics in Algorithm Design
Combinatorics theory counts, selects, and arranges numbers or objects. First, consider these programming-related questions. Four-digit PIN security? what options exist? What if the PIN has a prefix? How to locate all decimal number pairs?
Combinatorics questions. Software engineering jobs often require counting items. Combinatorics counts elements without counting them one by one or through other verbose approaches, therefore it enables us to offer minimum and efficient solutions to real-world situations. Combinatorics helps us make reliable decision tests without missing edge cases. Write a program to see if three inputs form a triangle. This is a question I commonly ask in software engineering interviews.
Graph theory is a subfield of combinatorics. Graph theory is used in computerized road maps and social media apps.
Logarithms and Geometry Understanding
Geometry studies shapes, angles, and sizes. Cartesian geometry involves representing geometric objects in multidimensional planes. Geometry is useful for programming. Cartesian geometry is useful for vector graphics, game development, and low-level computer graphics. We can simply work with 2D and 3D arrays as plane axes.
GetWindowRect is a Windows GUI SDK geometric object.
High-level GUI SDKs and libraries use geometric notions like coordinates, dimensions, and forms, therefore knowing geometry speeds up work with computer graphics APIs.
How does exponentiation's inverse function work? Logarithm is exponentiation's inverse function. Logarithm helps programmers find efficient algorithms and solve calculations. Writing efficient code involves finding algorithms with logarithmic temporal complexity. Programmers prefer binary search (O(log n)) over linear search (O(n)). Git source specifies O(log n):
Logarithms aid with programming math. Metas Watchman uses a logarithmic utility function to find the next power of two.
Employing Mathematical Data Structures
Programmers must know data structures to develop clean, efficient code. Stack, queue, and hashmap are computer science basics. Sets and graphs are discrete arithmetic data structures. Most computer languages include a set structure to hold distinct data entries. In most computer languages, graphs can be represented using neighboring lists or objects.
Using sets as deduped lists is powerful because set implementations allow iterators. Instead of a list (or array), store WebSocket connections in a set.
Most interviewers ask graph theory questions, yet current software engineers don't practice algorithms. Graph theory challenges become obligatory in IT firm interviews.
Recognizing Applications of Recursion
A function in programming isolates input(s) and output(s) (s). Programming functions may have originated from mathematical function theories. Programming and math functions are different but similar. Both function types accept input and return value.
Recursion involves calling the same function inside another function. In its implementation, you'll call the Fibonacci sequence. Recursion solves divide-and-conquer software engineering difficulties and avoids code repetition. I recently built the following recursive Dart code to render a Flutter multi-depth expanding list UI:
Recursion is not the natural linear way to solve problems, hence thinking recursively is difficult. Everything becomes clear when a mathematical function definition includes a base case and recursive call.
Conclusion
Every codebase uses arithmetic operators, relational operators, and expressions. To build mathematical expressions, we typically employ log, ceil, floor, min, max, etc. Combinatorics, geometry, data structures, and recursion help implement algorithms. Unless you operate in a pure mathematical domain, you may not use calculus, limits, and other complex math in daily programming (i.e., a game engine). These principles are fundamental for daily programming activities.
Master the above math fundamentals to build clean, efficient code.

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
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Sanjay Priyadarshi
3 years ago
Meet a Programmer Who Turned Down Microsoft's $10,000,000,000 Acquisition Offer
Failures inspire young developers
Jason citron created many products.
These products flopped.
Microsoft offered $10 billion for one of these products.
He rejected the offer since he was so confident in his success.
Let’s find out how he built a product that is currently valued at $15 billion.
Early in his youth, Jason began learning to code.
Jason's father taught him programming and IT.
His father wanted to help him earn money when he needed it.
Jason created video games and websites in high school.
Jason realized early on that his IT and programming skills could make him money.
Jason's parents misjudged his aptitude for programming.
Jason frequented online programming communities.
He looked for web developers. He created websites for those people.
His parents suspected Jason sold drugs online. When he said he used programming to make money, they were shocked.
They helped him set up a PayPal account.
Florida higher education to study video game creation
Jason never attended an expensive university.
He studied game design in Florida.
“Higher Education is an interesting part of society… When I work with people, the school they went to never comes up… only thing that matters is what can you do…At the end of the day, the beauty of silicon valley is that if you have a great idea and you can bring it to the life, you can convince a total stranger to give you money and join your project… This notion that you have to go to a great school didn’t end up being a thing for me.”
Jason's life was altered by Steve Jobs' keynote address.
After graduating, Jason joined an incubator.
Jason created a video-dating site first.
Bad idea.
Nobody wanted to use it when it was released, so they shut it down.
He made a multiplayer game.
It was released on Bebo. 10,000 people played it.
When Steve Jobs unveiled the Apple app store, he stopped playing.
The introduction of the app store resembled that of a new gaming console.
Jason's life altered after Steve Jobs' 2008 address.
“Whenever a new video game console is launched, that’s the opportunity for a new video game studio to get started, it’s because there aren’t too many games available…When a new PlayStation comes out, since it’s a new system, there’s only a handful of titles available… If you can be a launch title you can get a lot of distribution.”
Apple's app store provided a chance to start a video game company.
They released an app after 5 months of work.
Aurora Feint is the game.
Jason believed 1000 players in a week would be wonderful. A thousand players joined in the first hour.
Over time, Aurora Feints' game didn't gain traction. They don't make enough money to keep playing.
They could only make enough for one month.
Instead of buying video games, buy technology
Jason saw that they established a leaderboard, chat rooms, and multiplayer capabilities and believed other developers would want to use these.
They opted to sell the prior game's technology.
OpenFeint.
Assisting other game developers
They had no money in the bank to create everything needed to make the technology user-friendly.
Jason and Daniel designed a website saying:
“If you’re making a video game and want to have a drop in multiplayer support, you can use our system”
TechCrunch covered their website launch, and they gained a few hundred mailing list subscribers.
They raised seed funding with the mailing list.
Nearly all iPhone game developers started adopting the Open Feint logo.
“It was pretty wild… It was really like a whole social platform for people to play with their friends.”
What kind of a business model was it?
OpenFeint originally planned to make the software free for all games. As the game gained popularity, they demanded payment.
They later concluded it wasn't a good business concept.
It became free eventually.
Acquired for $104 million
Open Feint's users and employees grew tremendously.
GREE bought OpenFeint for $104 million in April 2011.
GREE initially committed to helping Jason and his team build a fantastic company.
Three or four months after the acquisition, Jason recognized they had a different vision.
He quit.
Jason's Original Vision for the iPad
Jason focused on distribution in 2012 to help businesses stand out.
The iPad market and user base were growing tremendously.
Jason said the iPad may replace mobile gadgets.
iPad gamers behaved differently than mobile gamers.
People sat longer and experienced more using an iPad.
“The idea I had was what if we built a gaming business that was more like traditional video games but played on tablets as opposed to some kind of mobile game that I’ve been doing before.”
Unexpected insight after researching the video game industry
Jason learned from studying the gaming industry that long-standing companies had advantages beyond a single release.
Previously, long-standing video game firms had their own distribution system. This distribution strategy could buffer time between successful titles.
Sony, Microsoft, and Valve all have gaming consoles and online stores.
So he built a distribution system.
He created a group chat app for gamers.
He envisioned a team-based multiplayer game with text and voice interaction.
His objective was to develop a communication network, release more games, and start a game distribution business.
Remaking the video game League of Legends
Jason and his crew reimagined a League of Legends game mode for 12-inch glass.
They adapted the game for tablets.
League of Legends was PC-only.
So they rebuilt it.
They overhauled the game and included native mobile experiences to stand out.
Hammer and Chisel was the company's name.
18 people worked on the game.
The game was funded. The game took 2.5 years to make.
Was the game a success?
July 2014 marked the game's release. The team's hopes were dashed.
Critics initially praised the game.
Initial installation was widespread.
The game failed.
As time passed, the team realized iPad gaming wouldn't increase much and mobile would win.
Jason was given a fresh idea by Stan Vishnevskiy.
Stan Vishnevskiy was a corporate engineer.
He told Jason about his plan to design a communication app without a game.
This concept seeded modern strife.
“The insight that he really had was to put a couple of dots together… we’re seeing our customers communicating around our own game with all these different apps and also ourselves when we’re playing on PC… We should solve that problem directly rather than needing to build a new game…we should start making it on PC.”
So began Discord.
Online socializing with pals was the newest trend.
Jason grew up playing video games with his friends.
He never played outside.
Jason had many great moments playing video games with his closest buddy, wife, and brother.
Discord was about providing a location for you and your group to speak and hang out.
Like a private cafe, bedroom, or living room.
Discord was developed for you and your friends on computers and phones.
You can quickly call your buddies during a game to conduct a conference call. Put the call on speaker and talk while playing.
Discord wanted to give every player a unique experience. Because coordinating across apps was a headache.
The entire team started concentrating on Discord.
Jason decided Hammer and Chisel would focus on their chat app.
Jason didn't want to make a video game.
How Discord attracted the appropriate attention
During the first five months, the entire team worked on the game and got feedback from friends.
This ensures product improvement. As a result, some teammates' buddies started utilizing Discord.
The team knew it would become something, but the result was buggy. App occasionally crashed.
Jason persuaded a gamer friend to write on Reddit about the software.
New people would find Discord. Why not?
Reddit users discovered Discord and 50 started using it frequently.
Discord was launched.
Rejecting the $10 billion acquisition proposal
Discord has increased in recent years.
It sends billions of messages.
Discord's users aren't tracked. They're privacy-focused.
Purchase offer
Covid boosted Discord's user base.
Weekly, billions of messages were transmitted.
Microsoft offered $10 billion for Discord in 2021.
Jason sold Open Feint for $104m in 2011.
This time, he believed in the product so much that he rejected Microsoft's offer.
“I was talking to some people in the team about which way we could go… The good thing was that most of the team wanted to continue building.”
Last time, Discord was valued at $15 billion.
Discord raised money on March 12, 2022.
The $15 billion corporation raised $500 million in 2021.

Nir Zicherman
3 years ago
The Great Organizational Conundrum
Only two of the following three options can be achieved: consistency, availability, and partition tolerance
Someone told me that growing from 30 to 60 is the biggest adjustment for a team or business.
I remember thinking, That's random. Each company is unique. I've seen teams of all types confront the same issues during development periods. With new enterprises starting every year, we should be better at navigating growing difficulties.
As a team grows, its processes and systems break down, requiring reorganization or declining results. Why always? Why isn't there a perfect scaling model? Why hasn't that been found?
The Three Things Productive Organizations Must Have
Any company should be efficient and productive. Three items are needed:
First, it must verify that no two team members have conflicting information about the roadmap, strategy, or any input that could affect execution. Teamwork is required.
Second, it must ensure that everyone can receive the information they need from everyone else quickly, especially as teams become more specialized (an inevitability in a developing organization). It requires everyone's accessibility.
Third, it must ensure that the organization can operate efficiently even if a piece is unavailable. It's partition-tolerant.
From my experience with the many teams I've been on, invested in, or advised, achieving all three is nearly impossible. Why a perfect organization model cannot exist is clear after analysis.
The CAP Theorem: What is it?
Eric Brewer of Berkeley discovered the CAP Theorem, which argues that a distributed data storage should have three benefits. One can only have two at once.
The three benefits are consistency, availability, and partition tolerance, which implies that even if part of the system is offline, the remainder continues to work.
This notion is usually applied to computer science, but I've realized it's also true for human organizations. In a post-COVID world, many organizations are hiring non-co-located staff as they grow. CAP Theorem is more important than ever. Growing teams sometimes think they can develop ways to bypass this law, dooming themselves to a less-than-optimal team dynamic. They should adopt CAP to maximize productivity.
Path 1: Consistency and availability equal no tolerance for partitions
Let's imagine you want your team to always be in sync (i.e., for someone to be the source of truth for the latest information) and to be able to share information with each other. Only division into domains will do.
Numerous developing organizations do this, especially after the early stage (say, 30 people) when everyone may wear many hats and be aware of all the moving elements. After a certain point, it's tougher to keep generalists aligned than to divide them into specialized tasks.
In a specialized, segmented team, leaders optimize consistency and availability (i.e. every function is up-to-speed on the latest strategy, no one is out of sync, and everyone is able to unblock and inform everyone else).
Partition tolerance suffers. If any component of the organization breaks down (someone goes on vacation, quits, underperforms, or Gmail or Slack goes down), productivity stops. There's no way to give the team stability, availability, and smooth operation during a hiccup.
Path 2: Partition Tolerance and Availability = No Consistency
Some businesses avoid relying too heavily on any one person or sub-team by maximizing availability and partition tolerance (the organization continues to function as a whole even if particular components fail). Only redundancy can do that. Instead of specializing each member, the team spreads expertise so people can work in parallel. I switched from Path 1 to Path 2 because I realized too much reliance on one person is risky.
What happens after redundancy? Unreliable. The more people may run independently and in parallel, the less anyone can be the truth. Lack of alignment or updated information can lead to people executing slightly different strategies. So, resources are squandered on the wrong work.
Path 3: Partition and Consistency "Tolerance" equates to "absence"
The third, least-used path stresses partition tolerance and consistency (meaning answers are always correct and up-to-date). In this organizational style, it's most critical to maintain the system operating and keep everyone aligned. No one is allowed to read anything without an assurance that it's up-to-date (i.e. there’s no availability).
Always short-lived. In my experience, a business that prioritizes quality and scalability over speedy information transmission can get bogged down in heavy processes that hinder production. Large-scale, this is unsustainable.
Accepting CAP
When two puzzle pieces fit, the third won't. I've watched developing teams try to tackle these difficulties, only to find, as their ancestors did, that they can never be entirely solved. Idealized solutions fail in reality, causing lost effort, confusion, and lower production.
As teams develop and change, they should embrace CAP, acknowledge there is a limit to productivity in a scaling business, and choose the best two-out-of-three path.
Matt Nutsch
2 years ago
Most people are unaware of how artificial intelligence (A.I.) is changing the world.
Recently, I saw an interesting social media post. In an entrepreneurship forum. A blogger asked for help because he/she couldn't find customers. I now suspect that the writer’s occupation is being disrupted by A.I.
Introduction
Artificial Intelligence (A.I.) has been a hot topic since the 1950s. With recent advances in machine learning, A.I. will touch almost every aspect of our lives. This article will discuss A.I. technology and its social and economic implications.
What's AI?
A computer program or machine with A.I. can think and learn. In general, it's a way to make a computer smart. Able to understand and execute complex tasks. Machine learning, NLP, and robotics are common types of A.I.
AI's global impact
AI will change the world, but probably faster than you think. A.I. already affects our daily lives. It improves our decision-making, efficiency, and productivity.
A.I. is transforming our lives and the global economy. It will create new business and job opportunities but eliminate others. Affected workers may face financial hardship.
AI examples:
OpenAI's GPT-3 text-generation
Developers can train, deploy, and manage models on GPT-3. It handles data preparation, model training, deployment, and inference for machine learning workloads. GPT-3 is easy to use for both experienced and new data scientists.
My team conducted an experiment. We needed to generate some blog posts for a website. We hired a blogger on Upwork. OpenAI created a blog post. The A.I.-generated blog post was of higher quality and lower cost.
MidjourneyAI's Art Contests
AI already affects artists. Artists use A.I. to create realistic 3D images and videos for digital art. A.I. is also used to generate new art ideas and methods.
MidjourneyAI and GigapixelAI won a contest last month. It's AI. created a beautiful piece of art that captured the contest's spirit. AI triumphs. It could open future doors.
After the art contest win, I registered to try out these new image generating A.I.s. In the MidjourneyAI chat forum, I noticed an artist's plea. The artist begged others to stop flooding RedBubble with AI-generated art.
Shutterstock and Getty Images have halted user uploads. AI-generated images flooded online marketplaces.
Imagining Videos with Meta
Meta released Make-a-Video this week. It's an A.I. app that creates videos from text. What you type creates a video.
This technology will impact TV, movies, and video games greatly. Imagine a movie or game that's personalized to your tastes. It's closer than you think.
Uses and Abuses of Deepfakes
Deepfake videos are computer-generated images of people. AI creates realistic images and videos of people.
Deepfakes are entertaining but have social implications. Porn introduced deepfakes in 2017. People put famous faces on porn actors and actresses without permission.
Soon, deepfakes were used to show dead actors/actresses or make them look younger. Carrie Fischer was included in films after her death using deepfake technology.
Deepfakes can be used to create fake news or manipulate public opinion, according to an AI.
Voices for Darth Vader and Iceman
James Earl Jones, who voiced Darth Vader, sold his voice rights this week. Aged actor won't be in those movies. Respeecher will use AI to mimic Jones's voice. This technology could change the entertainment industry. One actor can now voice many characters.
AI can generate realistic voice audio from text. Top Gun 2 actor Val Kilmer can't speak for medical reasons. Sonantic created Kilmer's voice from the movie script. This entertaining technology has social implications. It blurs authentic recordings and fake media.
Medical A.I. fights viruses
A team of Chinese scientists used machine learning to predict effective antiviral drugs last year. They started with a large dataset of virus-drug interactions. Researchers combined that with medication and virus information. Finally, they used machine learning to predict effective anti-virus medicines. This technology could solve medical problems.
AI ideas AI-generated Itself
OpenAI's GPT-3 predicted future A.I. uses. Here's what it told me:
AI will affect the economy. Businesses can operate more efficiently and reinvest resources with A.I.-enabled automation. AI can automate customer service tasks, reducing costs and improving satisfaction.
A.I. makes better pricing, inventory, and marketing decisions. AI automates tasks and makes decisions. A.I.-powered robots could help the elderly or disabled. Self-driving cars could reduce accidents.
A.I. predictive analytics can predict stock market or consumer behavior trends and patterns. A.I. also personalizes recommendations. sways. A.I. recommends products and movies. AI can generate new ideas based on data analysis.
Conclusion
A.I. will change business as it becomes more common. It will change how we live and work by creating growth and prosperity.
Exciting times, but also one which should give us all pause. Technology can be good or evil. We must use new technologies ethically, fairly, and honestly.
“The author generated some sentences in this text in part with GPT-3, OpenAI’s large-scale language-generation model. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication. The text of this post was further edited using HemingWayApp. Many of the images used were generated using A.I. as described in the captions.”