More on Technology
Waleed Rikab, PhD
3 years ago
The Enablement of Fraud and Misinformation by Generative AI What You Should Understand
Recent investigations have shown that generative AI can boost hackers and misinformation spreaders.
Since its inception in late November 2022, OpenAI's ChatGPT has entertained and assisted many online users in writing, coding, task automation, and linguistic translation. Given this versatility, it is maybe unsurprising but nonetheless regrettable that fraudsters and mis-, dis-, and malinformation (MDM) spreaders are also considering ChatGPT and related AI models to streamline and improve their operations.
Malign actors may benefit from ChatGPT, according to a WithSecure research. ChatGPT promises to elevate unlawful operations across many attack channels. ChatGPT can automate spear phishing attacks that deceive corporate victims into reading emails from trusted parties. Malware, extortion, and illicit fund transfers can result from such access.
ChatGPT's ability to simulate a desired writing style makes spear phishing emails look more genuine, especially for international actors who don't speak English (or other languages like Spanish and French).
This technique could let Russian, North Korean, and Iranian state-backed hackers conduct more convincing social engineering and election intervention in the US. ChatGPT can also create several campaigns and various phony online personas to promote them, making such attacks successful through volume or variation. Additionally, image-generating AI algorithms and other developing techniques can help these efforts deceive potential victims.
Hackers are discussing using ChatGPT to install malware and steal data, according to a Check Point research. Though ChatGPT's scripts are well-known in the cyber security business, they can assist amateur actors with little technical understanding into the field and possibly develop their hacking and social engineering skills through repeated use.
Additionally, ChatGPT's hacking suggestions may change. As a writer recently indicated, ChatGPT's ability to blend textual and code-based writing might be a game-changer, allowing the injection of innocent content that would subsequently turn out to be a malicious script into targeted systems. These new AI-powered writing- and code-generation abilities allow for unique cyber attacks, regardless of viability.
OpenAI fears ChatGPT usage. OpenAI, Georgetown University's Center for Security and Emerging Technology, and Stanford's Internet Observatory wrote a paper on how AI language models could enhance nation state-backed influence operations. As a last resort, the authors consider polluting the internet with radioactive or misleading data to ensure that AI language models produce outputs that other language models can identify as AI-generated. However, the authors of this paper seem unaware that their "solution" might cause much worse MDM difficulties.
Literally False News
The public argument about ChatGPTs content-generation has focused on originality, bias, and academic honesty, but broader global issues are at stake. ChatGPT can influence public opinion, troll individuals, and interfere in local and national elections by creating and automating enormous amounts of social media material for specified audiences.
ChatGPT's capacity to generate textual and code output is crucial. ChatGPT can write Python scripts for social media bots and give diverse content for repeated posts. The tool's sophistication makes it irrelevant to one's language skills, especially English, when writing MDM propaganda.
I ordered ChatGPT to write a news piece in the style of big US publications declaring that Ukraine is on the verge of defeat in its fight against Russia due to corruption, desertion, and exhaustion in its army. I also gave it a fake reporter's byline and an unidentified NATO source's remark. The outcome appears convincing:
Worse, terrible performers can modify this piece to make it more credible. They can edit the general's name or add facts about current wars. Furthermore, such actors can create many versions of this report in different forms and distribute them separately, boosting its impact.
In this example, ChatGPT produced a news story regarding (fictional) greater moviegoer fatality rates:
Editing this example makes it more plausible. Dr. Jane Smith, the putative author of the medical report, might be replaced with a real-life medical person or a real victim of this supposed medical hazard.
Can deceptive texts be found? Detecting AI text is behind AI advancements. Minor AI-generated text alterations can upset these technologies.
Some OpenAI individuals have proposed covert methods to watermark AI-generated literature to prevent its abuse. AI models would create information that appears normal to humans but would follow a cryptographic formula that would warn other machines that it was AI-made. However, security experts are cautious since manually altering the content interrupts machine and human detection of AI-generated material.
How to Prepare
Cyber security and IT workers can research and use generative AI models to fight spear fishing and extortion. Governments may also launch MDM-defence projects.
In election cycles and global crises, regular people may be the most vulnerable to AI-produced deceit. Until regulation or subsequent technical advances, individuals must recognize exposure to AI-generated fraud, dating scams, other MDM activities.
A three-step verification method of new material in suspicious emails or social media posts can help identify AI content and manipulation. This three-step approach asks about the information's distribution platform (is it reliable? ), author (is the reader familiar with them? ), and plausibility given one's prior knowledge of the topic.
Consider a report by a trusted journalist that makes shocking statements in their typical manner. AI-powered fake news may be released on an unexpected platform, such as a newly created Facebook profile. However, if it links to a known media source, it is more likely to be real.
Though hard and subjective, this verification method may be the only barrier against manipulation for now.
AI language models:
How to Recognize an AI-Generated Article ChatGPT, the popular AI-powered chatbot, can and likely does generate medium.com-style articles.
AI-Generated Text Detectors Fail. Do This. Online tools claim to detect ChatGPT output. Even with superior programming, I tested some of these tools. pub
Why Original Writers Matter Despite AI Language Models Creative writers may never be threatened by AI language models.
Muhammad Rahmatullah
3 years ago
The Pyramid of Coding Principles
A completely operating application requires many processes and technical challenges. Implementing coding standards can make apps right, work, and faster.
With years of experience working in software houses. Many client apps are scarcely maintained.
Why are these programs "barely maintainable"? If we're used to coding concepts, we can probably tell if an app is awful or good from its codebase.
This is how I coded much of my app.
Make It Work
Before adopting any concept, make sure the apps are completely functional. Why have a fully maintained codebase if the app can't be used?
The user doesn't care if the app is created on a super server or uses the greatest coding practices. The user just cares if the program helps them.
After the application is working, we may implement coding principles.
You Aren’t Gonna Need It
As a junior software engineer, I kept unneeded code, components, comments, etc., thinking I'd need them later.
In reality, I never use that code for weeks or months.
First, we must remove useless code from our primary codebase. If you insist on keeping it because "you'll need it later," employ version control.
If we remove code from our codebase, we can quickly roll back or copy-paste the previous code without preserving it permanently.
The larger the codebase, the more maintenance required.
Keep It Simple Stupid
Indeed. Keep things simple.
Why complicate something if we can make it simpler?
Our code improvements should lessen the server load and be manageable by others.
If our code didn't pass those benchmarks, it's too convoluted and needs restructuring. Using an open-source code critic or code smell library, we can quickly rewrite the code.
Simpler codebases and processes utilize fewer server resources.
Don't Repeat Yourself
Have you ever needed an action or process before every action, such as ensuring the user is logged in before accessing user pages?
As you can see from the above code, I try to call is user login? in every controller action, and it should be optimized, because if we need to rename the method or change the logic, etc. We can improve this method's efficiency.
We can write a constructor/middleware/before action that calls is_user_login?
The code is more maintainable and readable after refactoring.
Each programming language or framework handles this issue differently, so be adaptable.
Clean Code
Clean code is a broad notion that you've probably heard of before.
When creating a function, method, module, or variable name, the first rule of clean code is to be precise and simple.
The name should express its value or logic as a whole, and follow code rules because every programming language is distinct.
If you want to learn more about this topic, I recommend reading https://www.amazon.com/Clean-Code-Handbook-Software-Craftsmanship/dp/0132350882.
Standing On The Shoulder of Giants
Use industry standards and mature technologies, not your own(s).
There are several resources that explain how to build boilerplate code with tools, how to code with best practices, etc.
I propose following current conventions, best practices, and standardization since we shouldn't innovate on top of them until it gives us a competitive edge.
Boy Scout Rule
What reduces programmers' productivity?
When we have to maintain or build a project with messy code, our productivity decreases.
Having to cope with sloppy code will slow us down (shame of us).
How to cope? Uncle Bob's book says, "Always leave the campground cleaner than you found it."
When developing new features or maintaining current ones, we must improve our codebase. We can fix minor issues too. Renaming variables, deleting whitespace, standardizing indentation, etc.
Make It Fast
After making our code more maintainable, efficient, and understandable, we can speed up our app.
Whether it's database indexing, architecture, caching, etc.
A smart craftsman understands that refactoring takes time and it's preferable to balance all the principles simultaneously. Don't YAGNI phase 1.
Using these ideas in each iteration/milestone, while giving the bottom items less time/care.
You can check one of my articles for further information. https://medium.com/life-at-mekari/why-does-my-website-run-very-slowly-and-how-do-i-optimize-it-for-free-b21f8a2f0162
Thomas Smith
3 years ago
ChatGPT Is Experiencing a Lightbulb Moment
Why breakthrough technologies must be accessible
ChatGPT has exploded. Over 1 million people have used the app, and coding sites like Stack Overflow have banned its answers. It's huge.
I wouldn't have called that as an AI researcher. ChatGPT uses the same GPT-3 technology that's been around for over two years.
More than impressive technology, ChatGPT 3 shows how access makes breakthroughs usable. OpenAI has finally made people realize the power of AI by packaging GPT-3 for normal users.
We think of Thomas Edison as the inventor of the lightbulb, not because he invented it, but because he popularized it.
Going forward, AI companies that make using AI easy will thrive.
Use-case importance
Most modern AI systems use massive language models. These language models are trained on 6,000+ years of human text.
GPT-3 ate 8 billion pages, almost every book, and Wikipedia. It created an AI that can write sea shanties and solve coding problems.
Nothing new. I began beta testing GPT-3 in 2020, but the system's basics date back further.
Tools like GPT-3 are hidden in many apps. Many of the AI writing assistants on this platform are just wrappers around GPT-3.
Lots of online utilitarian text, like restaurant menu summaries or city guides, is written by AI systems like GPT-3. You've probably read GPT-3 without knowing it.
Accessibility
Why is ChatGPT so popular if the technology is old?
ChatGPT makes the technology accessible. Free to use, people can sign up and text with the chatbot daily. ChatGPT isn't revolutionary. It does it in a way normal people can access and be amazed by.
Accessibility isn't easy. OpenAI's Sam Altman tweeted that opening ChatGPT to the public increased computing costs.
Each chat costs "low-digit cents" to process. OpenAI probably spends several hundred thousand dollars a day to keep ChatGPT running, with no immediate business case.
Academic researchers and others who developed GPT-3 couldn't afford it. Without resources to make technology accessible, it can't be used.
Retrospective
This dynamic is old. In the history of science, a researcher with a breakthrough idea was often overshadowed by an entrepreneur or visionary who made it accessible to the public.
We think of Thomas Edison as the inventor of the lightbulb. But really, Vasilij Petrov, Thomas Wright, and Joseph Swan invented the lightbulb. Edison made technology visible and accessible by electrifying public buildings, building power plants, and wiring.
Edison probably lost a ton of money on stunts like building a power plant to light JP Morgan's home, the NYSE, and several newspaper headquarters.
People wanted electric lights once they saw their benefits. By making the technology accessible and visible, Edison unlocked a hugely profitable market.
Similar things are happening in AI. ChatGPT shows that developing breakthrough technology in the lab or on B2B servers won't change the culture.
AI must engage people's imaginations to become mainstream. Before the tech impacts the world, people must play with it and see its revolutionary power.
As the field evolves, companies that make the technology widely available, even at great cost, will succeed.
OpenAI's compute fees are eye-watering. Revolutions are costly.
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Theresa W. Carey
3 years ago
How Payment for Order Flow (PFOF) Works
What is PFOF?
PFOF is a brokerage firm's compensation for directing orders to different parties for trade execution. The brokerage firm receives fractions of a penny per share for directing the order to a market maker.
Each optionable stock could have thousands of contracts, so market makers dominate options trades. Order flow payments average less than $0.50 per option contract.
Order Flow Payments (PFOF) Explained
The proliferation of exchanges and electronic communication networks has complicated equity and options trading (ECNs) Ironically, Bernard Madoff, the Ponzi schemer, pioneered pay-for-order-flow.
In a December 2000 study on PFOF, the SEC said, "Payment for order flow is a method of transferring trading profits from market making to brokers who route customer orders to specialists for execution."
Given the complexity of trading thousands of stocks on multiple exchanges, market making has grown. Market makers are large firms that specialize in a set of stocks and options, maintaining an inventory of shares and contracts for buyers and sellers. Market makers are paid the bid-ask spread. Spreads have narrowed since 2001, when exchanges switched to decimals. A market maker's ability to play both sides of trades is key to profitability.
Benefits, requirements
A broker receives fees from a third party for order flow, sometimes without a client's knowledge. This invites conflicts of interest and criticism. Regulation NMS from 2005 requires brokers to disclose their policies and financial relationships with market makers.
Your broker must tell you if it's paid to send your orders to specific parties. This must be done at account opening and annually. The firm must disclose whether it participates in payment-for-order-flow and, upon request, every paid order. Brokerage clients can request payment data on specific transactions, but the response takes weeks.
Order flow payments save money. Smaller brokerage firms can benefit from routing orders through market makers and getting paid. This allows brokerage firms to send their orders to another firm to be executed with other orders, reducing costs. The market maker or exchange benefits from additional share volume, so it pays brokerage firms to direct traffic.
Retail investors, who lack bargaining power, may benefit from order-filling competition. Arrangements to steer the business in one direction invite wrongdoing, which can erode investor confidence in financial markets and their players.
Pay-for-order-flow criticism
It has always been controversial. Several firms offering zero-commission trades in the late 1990s routed orders to untrustworthy market makers. During the end of fractional pricing, the smallest stock spread was $0.125. Options spreads widened. Traders found that some of their "free" trades cost them a lot because they weren't getting the best price.
The SEC then studied the issue, focusing on options trades, and nearly decided to ban PFOF. The proliferation of options exchanges narrowed spreads because there was more competition for executing orders. Options market makers said their services provided liquidity. In its conclusion, the report said, "While increased multiple-listing produced immediate economic benefits to investors in the form of narrower quotes and effective spreads, these improvements have been muted with the spread of payment for order flow and internalization."
The SEC allowed payment for order flow to continue to prevent exchanges from gaining monopoly power. What would happen to trades if the practice was outlawed was also unclear. SEC requires brokers to disclose financial arrangements with market makers. Since then, the SEC has watched closely.
2020 Order Flow Payment
Rule 605 and Rule 606 show execution quality and order flow payment statistics on a broker's website. Despite being required by the SEC, these reports can be hard to find. The SEC mandated these reports in 2005, but the format and reporting requirements have changed over the years, most recently in 2018.
Brokers and market makers formed a working group with the Financial Information Forum (FIF) to standardize order execution quality reporting. Only one retail brokerage (Fidelity) and one market maker remain (Two Sigma Securities). FIF notes that the 605/606 reports "do not provide the level of information that allows a retail investor to gauge how well a broker-dealer fills a retail order compared to the NBBO (national best bid or offer’) at the time the order was received by the executing broker-dealer."
In the first quarter of 2020, Rule 606 reporting changed to require brokers to report net payments from market makers for S&P 500 and non-S&P 500 equity trades and options trades. Brokers must disclose payment rates per 100 shares by order type (market orders, marketable limit orders, non-marketable limit orders, and other orders).
Richard Repetto, Managing Director of New York-based Piper Sandler & Co., publishes a report on Rule 606 broker reports. Repetto focused on Charles Schwab, TD Ameritrade, E-TRADE, and Robinhood in Q2 2020. Repetto reported that payment for order flow was higher in the second quarter than the first due to increased trading activity, and that options paid more than equities.
Repetto says PFOF contributions rose overall. Schwab has the lowest options rates, while TD Ameritrade and Robinhood have the highest. Robinhood had the highest equity rating. Repetto assumes Robinhood's ability to charge higher PFOF reflects their order flow profitability and that they receive a fixed rate per spread (vs. a fixed rate per share by the other brokers).
Robinhood's PFOF in equities and options grew the most quarter-over-quarter of the four brokers Piper Sandler analyzed, as did their implied volumes. All four brokers saw higher PFOF rates.
TD Ameritrade took the biggest income hit when cutting trading commissions in fall 2019, and this report shows they're trying to make up the shortfall by routing orders for additional PFOF. Robinhood refuses to disclose trading statistics using the same metrics as the rest of the industry, offering only a vague explanation on their website.
Summary
Payment for order flow has become a major source of revenue as brokers offer no-commission equity (stock and ETF) orders. For retail investors, payment for order flow poses a problem because the brokerage may route orders to a market maker for its own benefit, not the investor's.
Infrequent or small-volume traders may not notice their broker's PFOF practices. Frequent traders and those who trade larger quantities should learn about their broker's order routing system to ensure they're not losing out on price improvement due to a broker prioritizing payment for order flow.
This post is a summary. Read full article here
Matthew O'Riordan
3 years ago
Trends in SaaS Funding from 2016 to 2022
Christopher Janz of Point Nine Capital created the SaaS napkin in 2016. This post shows how founders have raised cash in the last 6 years. View raw data.
Round size
Unsurprisingly, round sizes have expanded and will taper down in 2022. In 2016, pre-seed rounds were $200k to $500k; currently, they're $1-$2m. Despite the macroeconomic scenario, Series A have expanded from $3m to $12m in 2016 to $6m and $18m in 2022.
Valuation
There are hints that valuations are rebounding this year. Pre-seed valuations in 2022 are $12m from $3m in 2016, and Series B prices are $270m from $100m in 2016.
Compared to public SaaS multiples, Series B valuations more closely reflect the market, but Seed and Series A prices seem to be inflated regardless of the market.
I'd like to know how each annual cohort performed for investors, based on the year they invested and the valuations. I can't access this information.
ARR
Seed firms' ARR forecasts have risen from $0 to $0.6m to $0 to $1m. 2016 expected $1.2m to $3m, 2021 $0.5m to $4m, and this year $0.5m to $2.5m, suggesting that Series A firms may raise with less ARR today. Series B minutes fell from $4.2m to $3m.
Capitalization Rate
2022 is the year that VCs start discussing capital efficiency in portfolio meetings. Given the economic shift in the markets and the stealthy VC meltdown, it's not surprising. Christopher Janz added capital efficiency to the SaaS Napkin as a new statistic for Series A (3.5x) and Series B. (2.5x). Your investors must live under a rock if they haven't asked about capital efficiency. If you're unsure:
The Capital Efficiency Ratio is the ratio of how much a company has spent growing revenue and how much they’re receiving in return. It is the broadest measure of company effectiveness in generating ARR
What next?
No one knows what's next, including me. All startup and growing enterprises around me are tightening their belts and extending their runways in anticipation of a difficult fundraising ride. If you're wanting to raise money but can wait, wait till the market is more stable and access to money is easier.
Jess Rifkin
3 years ago
As the world watches the Russia-Ukraine border situation, This bill would bar aid to Ukraine until the Mexican border is secured.
Although Mexico and Ukraine are thousands of miles apart, this legislation would link their responses.
Context
Ukraine was a Soviet republic until 1991. A significant proportion of the population, particularly in the east, is ethnically Russian. In February, the Russian military invaded Ukraine, intent on overthrowing its democratically elected government.
This could be the biggest European land invasion since WWII. In response, President Joe Biden sent 3,000 troops to NATO countries bordering Ukraine to help with Ukrainian refugees, with more troops possible if the situation worsened.
In July 2021, the US Border Patrol reported its highest monthly encounter total since March 2000. Some Republicans compare Biden's response to the Mexican border situation to his response to the Ukrainian border situation, though the correlation is unclear.
What the bills do
Two new Republican bills seek to link the US response to Ukraine to the situation in Mexico.
The Secure America's Borders First Act would prohibit federal funding for Ukraine until the US-Mexico border is “operationally controlled,” including a wall as promised by former President Donald Trump. (The bill even mandates a 30-foot-high wall.)
The USB (Ukraine and Southern Border) Act, introduced on February 8 by Rep. Matt Rosendale (R-MT0), would allow the US to support Ukraine, but only if the number of Armed Forces deployed there is less than the number deployed to the Mexican border. Madison Cawthorne introduced H.R. 6665 on February 9th (R-NC11).
What backers say
Supporters argue that even if the US should militarily assist Ukraine, our own domestic border situation should take precedence.
After failing to secure our own border and protect our own territorial integrity, ‘America Last' politicians on both sides of the aisle now tell us that we must do so for Ukraine. “Before rushing America into another foreign conflict over an Eastern European nation's border thousands of miles from our shores, they should first secure our southern border.”
“If Joe Biden truly cared about Americans, he would prioritize national security over international affairs,” Rep. Cawthorn said in a separate press release. The least we can do to secure our own country is send the same number of troops to the US-Mexico border to assist our border patrol agents working diligently to secure America.
What opponents say
The president has defended his Ukraine and Mexico policies, stating that both seek peace and diplomacy.
Our nations [the US and Mexico] have a long and complicated history, and we haven't always been perfect neighbors, but we have seen the power and purpose of cooperation,” Biden said in 2021. “We're safer when we work together, whether it's to manage our shared border or stop the pandemic. [In both the Obama and Biden administration], we made a commitment that we look at Mexico as an equal, not as somebody who is south of our border.”
No mistake: If Russia goes ahead with its plans, it will be responsible for a catastrophic and unnecessary war of choice. To protect our collective security, the United States and our allies are ready to defend every inch of NATO territory. We won't send troops into Ukraine, but we will continue to support the Ukrainian people... But, I repeat, Russia can choose diplomacy. It is not too late to de-escalate and return to the negotiating table.”
Odds of passage
The Secure America's Borders First Act has nine Republican sponsors. Either the House Armed Services or Foreign Affairs Committees may vote on it.
Rep. Paul Gosar, a Republican, co-sponsored the USB Act (R-AZ4). The House Armed Services Committee may vote on it.
With Republicans in control, passage is unlikely.