What Are Dynamic NFTs?

Non-fungible tokens, NFTs, are finally making their way into the mainstream after achieving widespread adoption among the Web3 community. Despite the recent boom and bust of crypto and the accompanying spotlights from media outlets, digital influencers, public figures, and professional athletes have continued to jump on the bandwagon of NFT collections. 

As a result, there remains an interest in NFTs as a prominent application of blockchain technology, which retains the speculative asset moniker. However, the first NFTs were simple: often 8-bit style pictures that could be considered novelties and may or may not “boom” in the future. 

Yet that was just the beginning of the NFT evolution which may change the broader financial markets as we approach 2023. Dynamic NFTs (dNFTs) are pushing the boundaries of the design space that NFTs address through their ability to adapt and change, responding to external data and events. 

This article gives a brief NFT overview and then explains how dNFTs can take the blockchain space to the next level by highlighting current and potential uses for dNFTs. 

NFTs in Brief

NFTs are unique digital assets held, managed, and exchanged on one or more blockchains. “Non-fungible” means that every NFT is differentiated from every other NFT, having a one-for-one token ID and unique contract address. From there, data, such as images, video, or other metadata, can be attached to the NFT, meaning it’s possible to own an NFT representing a unique digital object.  

The most common use case for an NFT has been digital art. An artist will mint a token representing a digital artwork, and a buyer can purchase the token giving them ownership. Once an NFT is minted, its token ID doesn’t change. In its most simple form, an NFT is a transferable token with a unique token ID. 

The metadata ascribed to the NFT, including the image, description, and much more, is 100% optional. As a result, this primary (static) NFT model can provide various benefits for digital artists worldwide. 

Before NFTs, digital artists could not stop or track the unauthorized distribution of their work because there was no method to distinguish the difference between digital files. Thus, no single authentic file could be “owned.” Now, digital creators can sell their art to fans and give them verifiable ownership.

Dynamic NFTs

Static NFTs are still the most common type of NFTs available and in circulation, used primarily for art projects and gaming collectibles, such as with NBA TopShot. But, beyond these uses, static NFTs provide a unique value proposition for digitizing real-world items like real estate deeds, patents, other intellectual property, and unique identifiers. 

However, the static NFT model is limited by its permanence. Once the metadata is attached to the token and minted on the blockchain, it cannot be changed. The data may require frequent updating, such as with real-world assets, progression-based video games, or blockchain-based fantasy sports leagues. 

A dNFT provides the best of both worlds, allowing the retention of a unique identifier while enabling an update to its metadata. In simple terms, a dNFT changes attributes based on external conditions.

dNFTs can be upgraded in several ways based on external conditions. The changes to a dynamic NFT are generally through metadata changes triggered by a linked smart contract. This is accomplished by encoding the automatic changes within the NFT’s smart contract, which instructs the underlying NFT on how and when the metadata should change.

Source: Chainlink

Other dynamic elements beyond metadata changes are possible. For example, dynamic NFTs can be automatically minted when certain conditions are met, such as when a player finds a hidden spot in an augmented-reality game. dNFTs also include “hidden traits,” which are manifested through user interactions rather than within the NFT’s metadata. dNFTs are wholly customizable. 

Use Cases of Dynamic NFTs

An NFT’s name is specified in its metadata. This is also where its traits are assigned, including any relevant file links. While its token ID provides a permanent identifier that verifies ownership, the metadata is the soul of the NFT. The metadata contains the elements that make the NFT useful.  

Artistic projects using NFTs often have a variety of traits, some rarer than others. These traits are placed within the NFT’s metadata and a link to a corresponding image or video. And with a dNFT, these traits can change based on external conditions. 

Progressive Gaming

This functionality benefits character progression, a core tenant of several blockchain game models. When a new player creates their playable, NFT-linked character, the character’s base-level statistics are reflected in the NFT’s metadata. However, as the player continues to level up, the metadata on their dNFT changes to reflect their progression, choices, and growing stats.  

Real-World Assets

A second use case for shifting metadata is the tokenization of real-world assets. For example, a dNFT reflecting a property reflects its age, maintenance history, sales history, market value, and so on. A static NFT could only take a single snapshot of the property at one point in time. 

Popular Examples of Today

Two prominent examples demonstrate to us the growing potential of dNFTs. 

Regenerative Resources’ Short Film dNFTs

Regenerative Resources Co (RRC) is focused on transforming degraded coastal land into highly productive seawater landscapes. RRC has announced that it will launch five short films in dNFT form, designed by prominent artists. 

The proceeds from the dNFTs will be used to grow 100 million mangroves within the space afforded by RRC’s current projects. 

Each dNFT will have a short film in its metadata, starting with a single frame of the film. Every time the dNFT is bought and resold, more frames of each movie will be added to the respective metadata. This addition will continue until the dNFT holder can view the short film. The metadata will also include the “producers,” or those who buy limited-edition posters.  

LaMelo Ball dNFTs

LaMelo Ball, a rising star of the NBA’s Charlotte Hornets, is one of the first professional athletes to create a pioneering dNFT linked to the Chainlink Sports Data Feeds oracle. According to Playground Studio, this dNFT is redefining player-fan relationships

Before his NBA award of 2021’s Rookie of the Year, fans minted 8,070 dNFTs of four different tiers. However, eight dNFTs recorded the player’s stats, including points, rebounds, and assists.

Holders receive special access to raffles and specific perks based on Ball’s season and lifetime performance. One of the premium eight NFTs, the “Gold Evolve,” came with a promise from the player that if he won the Rookie of the Year title, it would reflect a new image. When Ball won, the NFT image changed. 

Source: Opensea

These LaMelo Ball dNFTs are examples of how dNFTs can continuously change based on oracle-provided external data. With Ball’s dNFTs, the player’s stats are constantly updated on-chain, triggering updates, rewards, and more.

Closing Thoughts

NFTs are highly speculative assets, and dynamic NFTs have just started to appear. They’re more of a novelty for programmers and collectors, adding more functionality to the current generation of static NFTs containing mainly altered pictures or briefly shifting video.

However, dNFT’s underlying abilities have immense potential, especially when more oracles are added to blockchains, increasingly able to provide relevant and curated data. Furthermore, these oracles providing external data can effectively supercharge dNFTs as programmers learn to fuse changing data with NFTs. Mastering this foundation opens new doors for finance, insurance, real estate, gaming, investing, and more as we expand. 

Disclaimer: The information provided in this article is solely the author’s opinion and not investment advice – it is provided for educational purposes only. By using this, you agree that the information does not constitute any investment or financial instructions. Do conduct your own research and reach out to financial advisors before making any investment decisions.

The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment. Mr. Chalopin is Chairman of Deltec International Group, www.deltec.io

The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business. Mr. Trehan is a Senior VP at Deltec International Group, www.deltec.io

Web3’s Infrastructure

After covering all things blockchain for a few years, we’ve seen how the move toward Web3 is much more than the “magic” of digital money that many think on when they discuss cryptocurrencies. Web3 has the potential to solve the significant issues that plague the web and our world, regarding privacy, self-autonomy, and economics.  

The infrastructure behind Web3 will be a service that helps Web3 apps and their underlying blockchains perform better with amplified capabilities, and which is going to be a foundational pillar of Web3. There are now over 1,000 blockchains. This requires massive infrastructure. And infrastructure makes or breaks new projects.   

Inside Web3

We have previously written about Web3 and the pathway to get there from Web 1.0 that began in the 1990s.   

Web3 websites continue to be hosted on traditional web servers. However, the users own and operate some parts of the project, unlike the corporate oligarchy inherent in Web2. Web3 websites directly connect to underlying blockchain networks to facilitate user ownership. Typical blockchains used for this purpose are Ethereum, Binance, Solana, and Fantom.  

Let’s work through an example using a decentralized finance (Defi) website on the Fantom blockchain, SpiritSwap.  

Source: SpiritSwap

The SpiritSwap web application is hosted on a traditional Web2 server, which is running on Amazon Web Services(AWS). However, when a user wants to interact with SpiritSwap, they need to have a browser extension wallet, such as MetaMask, or a Coinbase Wallet, which connects to and authenticates their use of the web application.  

These wallets can be thought of as a universal single sign-on tool. Rather than a user logging onto SpiritSwap with their username and password under SpiritSwap’s control, the wallet itself logs in. The wallet also contains all the user’s digital assets (cryptocurrencies and NFTs) while simultaneously acting as the digital identity, represented by a user’s hexadecimal address that starts with “0x.” 

Once the wallet is connected, the user can exchange digital assets like a trader on the NYSE floor. 

Behind the scenes (on the backend), the user’s wallet is connecting directly with an additional server running the blockchain’s application, or a node. This stores data about the blockchain and communicates with the other blockchain network nodes, including the validators that create blocks.  

These application nodes use the same amount of electricity as a typical Web2 server. However, there is a need to access two servers: one running the web application and the other running the blockchain.  

At this point, digital infrastructure providers become essential. They must devise efficient and innovative server solutions. 

Web3 Demands Strong Infrastructure

Physical Servers

Although Web3 requires access to many servers, the Web3 movement is opposed to using the public cloud due to centralization concerns. 

Various Web3 projects, such as Solana, have been renting and buying several thousand “bare metal” (physical) servers from a variety of players. The leasing of these servers attracted the attention of Equinix Metal, who hosted “Uncensored,” the Infrastructure Blockchain event, to promote best practices in this growing space.  

Ankr’s Remote Procedure Call (RPC) service has served over 700 million monthly requests from Argentinian users, with similar numbers from Vietnam and Argentina. An RPC occurs when a computer program executes a procedure in a different address space, such as one a different computer in a shared network.   

Hetzner has a competitive infrastructure hardware product available for German and Finnish clients through its AX101 and AX161 configurations. Unfortunately, most bare metal servers stocked by providers do not match the ideal specs needed for Web3. 

Lower Redundancy

As peer-to-peer networks, blockchains are decentralized and distributed by their nature. This means that redundancy (backups) exists seamlessly within the network. If some physical hardware fails or a network outage happens, the blockchain itself remains virtually unharmed. 

In a traditional enterprise environment, it’s not uncommon to have multiple power supplies with layers of hardware to ensure network redundancy.  

Greater Disk Speed, Size, and Storage

We can imagine a blockchain like a growing stack of connected Lego bricks. The first brick is the “genesis block.” The stack will constantly grow from one side, and each block contains the group of transactions that form the distributed ledger. This is a huge amount of data that usually runs in LevelDB (an open-source NoSQL database), and it grows larger with every epoch (brief span of blockchain time).   

Unfortunately, Ankr demonstrated that most network-attached storage options and virtualization technologies were insufficient to keep up with the needs.  

This deficit means that most bare metal configurations using regular solid-state drives with less than 4TB of storage will not be sufficient for a high-traffic Web3 workload.

According to Ankr, 4TB of NVMe (non-volatile memory) solid-state storage is a minimum requirement. However, 8TB of NVMe per server for RPC nodes is preferable. In the case of archive nodes, which store entire copies of blockchains, between 12 and 30TB of NVMe per physical server is needed. Yet for some chains, even more is required.  

Web3’s Node Types

RPC Full NodeArchive NodeValidator Node
The most common node type.

Used by developers/projects to connect and interact with a blockchain.

Every use case for Web3/Defi/Metaverse needs access to other RPC full nodes.
Used by market research/analytics apps to track a blockchain’s activity.

Requires a lot of fast storage, starting with 12TB of NVMe.
Validators create the next block. 

For this, they receive crypto rewards from the network.In proof-of-stake (PoS) blockchains like Ethereum 2, Binance’s Smart Chain, and Solana, validators replace miners (i.e., Bitcoin).

Uses an enterprise-grade bare metal server or virtual server.

Low Latency and Speed Are Critical

For most Ethereum-based chains, a typical RPC full node uses about 50mbps of bandwidth. This usage means that 30TB of data transfer per month and per server is sufficient.

In the last year, the Argentine peso fell 36% in value against the US dollar. 

This has resulted in a switch from the peso to other currencies (many of them cryptos), and therefore 700 million RPC requests.  

As DeFi supplements or even replaces traditional finance, connections to proximity nodes, and low latency (low delay) connections become critical parts of financial infrastructure. Blockchain gaming applications that adopt NFTs for in-game purchases and other transactions demand low latency for their applications. 

Closing Thoughts

Web3 is the promising frontier of this decade. To be successful, digital infrastructure providers must offer new bare metal configurations which are quick and able to hold massive amounts of data while maintaining low latency. 

Web3 demands a new breed of digital infrastructure providers maximizing the utility of bare metal configurations for faster, larger, and more efficient data processing. Web2 shall likely and finally yield to Web3, but only after the infrastructure is built, and that depends on the forward-looking innovators amongst us. 

Disclaimer: The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment. Mr. Chalopin is Chairman of Deltec International Group, www.deltecbank.com.

The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business. Mr. Trehan is a Senior VP at Deltec International Group, www.deltecbank.com.

The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees.

Brain-Computer Interfaces and the Metaverse

What are the commercial promises of brain-computer interfaces, and how will they further connect us to the promises of the metaverse? These interfaces, initially sensory (on the scalp or skin), and possibly through brain implants in the future, could be the eventual platforms transforming all parts of our diverse societies. 

The Brain-Computer Merge

You may not have noticed, but with each passing day, we are slowly merging more and more with the technology around us. Our smartphones are our tools for instant communication and the answers to many of our questions, allowing us to focus on other things rather than that which occupied our minds in the past. 

We have implanted pacemakers and defibrillators that tell the cardiologist all about our hearts and correct our irregularities. We have implanted lenses in our eyes to fix vision issues. The technology around us now, especially with our smartphones, will not represent the most common interface in our future. 

What our smartphones do, and much more will likely be incorporated into our bodies. Though google glass was not a successful project, many of its users were the wrong targets, and it was also burdened with tech glitches and security concerns. It did, however, show that we could bring technology closer, supplying useful information and sending sound directly into the ear with bone conduction. 

Source: The Verge

As brain-computer interface (BCI) systems progress, they will be an essential step forward in the brain-computer merge. A BCI’s role is the interpretation of the user’s neural activity. A BCI is just part of an environment that is more wired, has more sensors, and is digitally connected.   

With the current generation of experimental brain-computer interfaces, using only their minds, humans can play video games, articulate prosthetic limbs, control their own limbs, work wheelchairs, and more. BCIs have the potential to communicate with patients that suffer from Alzheimer’s disease, head injuries, and stroke, allowing them to control computers that help them speak.  

BCI technology will likely take a turn for enhancing sensory connection and communication. The most common use for BCI technology is the directional control of a computer cursor. Imagine moving your mouse and clicking without the need for the mouse. 

This is already being done only with electrophysiological signals (brain and blood signals to a system of sensors). This BCI control system has already been utilized by users (both humans and animals) to control the external world without the need for conventional neuromuscular pathways (speech).  

Brain-Computer Interfaces Alongside the Metaverse

The metaverse is a fusing of the real and digital worlds. It’s either an entirely simulated digital environment, as is the case of virtual reality (VR), or an overlay of a digital experience to the real world with augmented reality (AR). 

Thought of in a different way, the metaverse can be a platform where users can feel the real through an animated or digital world encounter. The metaverse that combines augmented reality with the real world can give us more immersive, next-level platforms. The metaverse is intended to make our lives more natural and “realistic,” including socializing, work, and entertainment.  

Scientists, researchers, corporations, and entrepreneurs are making strides with their new and advanced applications. Many of these applications are intended to augment human abilities, fulfilling desires to be stronger, smarter, and better looking. 

Exoskeleton by SuitX

With the BCI connection, it’s believed that part of this initiative will transform technology, medicine, society, and the future. Current devices can cultivate human abilities that exceed the former standards and are not dissimilar to the great powers of Iron Man. SuitX’s Exoskeleton can reduce lower back loads by 60%.  

As these technologies continue to merge with BCIs, it’s believed that the opportunity to augment human capability will be even greater.  

Elon Musk’s Neuralink has been working on a consumer-intended high-bandwidth BCI that focuses on four parts of the brain. 

Source: Neuralink

Neuralink has shared their video of a macaque playing “MindPong” by way of chips embedded in a few regions of its brain. The primate was trained to play the game by simply thinking about moving its hands. The goal is for future “Neuralinks” to tie the brain to the body’s motor and sensory cortices, thereby enabling people with paraplegia the ability to walk again. 

Inside a Metaverse

Technical training inside a metaverse consists of providing technicians with advanced features and simulations capable of operating 3D representations of complex systems, instruments, or machinery. 

BCIs with simulation technology will combine to empower the metaverse, allowing remote support and maintenance of devices and equipment. This could be a matter of connecting with experts who would control the repair of the system by thinking about moving their own hands to make repairs. 

This would allow for the “switching on” of virtual reality engineers and technicians when an unforeseen repair occurs. It’s not so far of a step beyond this to think of the same procedure for doctors and surgeons.

Dating and socializing in virtual reality may become a common occurrence with virtual movies and museum tours. Such interactions could be enhanced with the direct brain interface that enriches the mind of our partners, adding to positive experiences from the external environment (“I wish you could see things from my point of view” would be possible).  

Closing Thoughts

Applications of brain-computer interfaces are spread across many fields and are not limited to military or medical purposes. The fullest realization of these technologies will certainly take time and incremental improvements, but they will be well-suited for the metaverse. 

This process will require significant testing and a long period of adoption. However, brain interfaces can be game changers in their lives and incredible experiences for many.  

We could eventually see a future that no longer has brain-computer interfaces but goes toward the next step of direct brain-to-brain connections. This new type of connection is a very exciting step that would bring humans closer together, allowing us to understand how we all experience the real and virtual worlds.  

Disclaimer: The information provided in this article is solely the author’s opinion and not investment advice – it is provided for educational purposes only. By using this, you agree that the information does not constitute any investment or financial instructions. Do conduct your own research and reach out to financial advisors before making any investment decisions.

The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment.  Mr. Chalopin is Chairman of Deltec International Group, www.deltecbank.com.

The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business.  Mr. Trehan is a Senior VP at Deltec International Group, www.deltecbank.com.

The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees.

The Convergence of Technology and Healthcare

We saw the changes to our lives with the Covid-19 pandemic playing the role of catalyst for changes in life sciences and healthcare. This article will discuss how new technologies, including blockchain, cybersecurity, and the needed talent behind these, are impacting the medical sector.

Recent Changes to Healthcare

We have seen how the past few years have been shaped by the Covid-19 pandemic, which disrupted and revolutionized nearly every sector of our economy. 

When we look at monetary investment, it’s evident that technology spending is focused on healthcare. A report from Bain and Co found that even with economic uncertainty, healthcare is still planning to invest in tech, with software being a top five strategic priority for 80% of providers and a top three for 40%. 

This spending is for several reasons: efficiency, cost reduction, and telemedicine, whether by phone or video. Heavy technology investment in the era of Covid-19 caused healthcare to leapfrog into patients’ homes. 

These changes will be the driver of healthcare’s growth for the next few years. Yet we need to have a strong understanding of how the consumer fits into this system of delivering service, what their preferences are, and the new habits they are forming.

Once Before, in the 1920s

Periods of economic and geopolitical uncertainty have led to healthcare advancements. 

In the 1920s, there were many geopolitical tensions that eventually led to wars, but throughout the decade and the rest of the 20th century, there were remarkable advances in medicine. 

The construction of hospitals that followed the passing of the Hill-Burton Act in 1946 made the foundation of our current health delivery system, the same way we saw our highway system and other infrastructure change the face of America and its economy. We’ll likely see a similar change around needed vaccines and other due innovations. 

Rather than creating roads, bridges, and buildings, we’ll see digital infrastructure. Out of the discovery of the first mRNA Covid vaccines, we’ll find many ways to accelerate the process through biotechnology and innovation. Technology is an added dimension to healthcare innovation that has appeared out of the Covid turmoil. When technology is added to the mix, we’re going to see some fantastic opportunities.  

The Covid Cause

It’s remarkable to think that a significant, globally impacting event is a catalyst that accelerates healthcare sector tech investment. If the necessary Covid closures were only for a single week, many of these changes would not have resulted. 

Doctor visits would have been pushed back for that week instead of finding a remote solution that was needed to provide the required services and the resulting changed behaviors they have brought. The R&D plans that are now part of biotech and medical companies would likely not have manifested. 

But we see that necessity is the mother of innovation, and because of Covid-19, these changes are incorporated and permanent. Many experts believe that the two years of Covid moved the industry ahead 5 to 10 years.

A Move Toward NFTs in Healthcare

Non-Fungible Tokens (NFTs) have been an investment darling in the art world but have yet to gain prominence much outside that and the collecting arenas. This lack of diversified uses is starting to change. Healthcare is up next. 

NFTs are an exciting area for healthcare services. It’s easy to imagine a world where an NFT can become a patient’s profile in healthcare. An NFT profile has the capability to carry personal information such as the entire genome and all medical history and payment information as a unique footprint.

An NFT can also provide the owner with a pathway to get them into the healthcare system and provide them with services. This information can be combined with the banking system making their help more viable. Imagine a health saving account tied directly to the NFT through an oracle (a third-party gateway).  

This will be able to allow someone to fund their health savings account through their W2-qualifying job. Charges that fit under the account can be automatically withdrawn. 

This kind of payment system is just starting to happen on the municipal level. Cities like New York and Miami have begun to move toward such a system, with Philadelphia and Dearborn, Michigan, signaling similar moves. It’s not far-fetched to imagine a similar action to healthcare payments. 

Cybersecurity in Healthcare

When there is human involvement, there is the potential for security vulnerabilities. The second issue that all companies are dealing with is finding the right talent that is capable of building systems and products able to protect company and personal data. There is an ongoing global shortage of nearly 3.5 million cybersecurity professionals across all industries, with 700,000 unfilled cybersecurity jobs in the US.  

Cybersecurity for healthcare also requires the development of technicians that can play defense, quickly responding to cyberattacks in real-time. Hacking is accelerating and is a top risk profile for many companies, not just in tech. 

Interestingly, one of hacking’s growing tools, AI, may also be its best solution as more information and services are digitized. Significant investment is happening in software projects that help protect and defend all data. In November 2022, Crunchbase showed 258 privacy startups that have raised over $4.3 billion, with $800 million of this total raised in the last year.  

Life sciences and healthcare are industries that drive policies and security. Many boards and audit committees in the healthcare and life science sectors are attempting to identify various cyber risks and vulnerabilities. It’s fully expected that the demand for cyber-fluent personnel will increase dramatically. 

Permanent Changes Coming to Healthcare

Tech is now taking over in several areas, including consumer electronics. Wearables and connected devices are becoming a more common source of medical information. Alivecor’s KardiaMobile device is a 6-lead EKG that can send information via smartphone directly to the patient’s cardiologist for review.  

Source: Alivecor

The Las Vegas consumer electronics show is filled with sensors, apps, and embedded personalization. This expansion of devices for our health will only increase as the 5G networks expand their reach across the United States. The impacts will be wide-ranging, but ultimately focus on enhancing our lives through tech. 

One crucial, long-term benefit is that we are now seeing the healthcare economy moving from a sickness focus to a wellness mindset. This change is easier to accomplish with technology as we can monitor our health and see when things change.  

Upcoming Healthcare Trends

The healthcare sector will first see a move toward modernization in human resources, finance, and procurement through cloud services. Moving all legacy enterprise systems to the cloud will take nearly ten years. 

Next, innovation must tackle the back office to front office connection, including consumer-level devices. We have been discussing healthcare costs for decades, and the tech is now available to make it more efficient. This change can drive out costs and potentially deliver care to all.  

Closing Thoughts

Technology in healthcare has been accelerated by Covid-19, pushing digital health access, and drug and vaccine innovation. These trends are altering research and development pathways for healthcare. 

NFTs have begun to enter the healthcare space and, in the future, will likely be a secure way to provide needed information to providers, including genome and medical history. Cybersecurity issues will come to the forefront in healthcare tech with more need for talent and solutions to keep users’ data secure. 

This need for talent will include the opportunity for tech to provide equitable solutions that lower costs and bring healthcare to all. A process of modernization that puts enterprise services on the cloud will be the biggest change we will see. Further, it will promote a focus of wellness over sickness as consumer devices become ubiquitous. 

Disclaimer: The information provided in this article is solely the author’s opinion and not investment advice – it is provided for educational purposes only. By using this, you agree that the information does not constitute any investment or financial instructions. Do conduct your own research and reach out to financial advisors before making any investment decisions.

The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment.  Mr. Chalopin is Chairman of Deltec International Group, www.deltecbank.com.

The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business.  Mr. Trehan is a Senior VP at Deltec International Group, www.deltecbank.com.

The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees.

Autonomous Ride-Hailing

Uber and Lyft have changed the short-distance ride-hailing market once belonging to the local and usual handful of taxi companies. As they took over these new markets, they also changed the way we thought about travel.

Further, asking friends for a ride to the airport is beginning to disappear with the onset of autonomous vehicles. Several new companies are testing this out, and some are in full operation in limited areas with complete, autonomous ride-share services. We take a deep dive into the current state of the autonomous ride-hailing market. 

The Rise of Autonomous Vehicles

Autonomous technology is the next stage for the travel industry. The growing success of the electric vehicle set the tone, even if battery costs have a long way down to go. But it’s better to call this one door leading to many. 

For example, artificial intelligence will play a crucial role in the use of autonomous ride-hailing. We have: route optimization, accident prevention, and maximized utilization (keeping all vehicles active). Not only does this lower costs for companies entering this space, it dramatically improves urban efficiency. 

ARK Investment Research has predicted that the price of autonomous electric vehicle transportation will fall to $0.25 per mile by 2030.

These three factors will drive the cost of ride-hailing services. However, industrialized countries will also see a massive reduction in the cost per mile as labor makes up over 70% of the cost, which is followed by the vehicle itself, and its fuel and maintenance. ARK Research has estimated that the price per mile could be reduced by up to 88% for an autonomous ride-hail.

The autonomous ride-share total addressable market (TAM) is estimated to reach between $11 and $12 trillion for two key reasons. 

1.     High utilization rates. Electric autonomous vehicles can provide rides to clients 24 hours a day, only offline during charging and maintenance times.  

2.     Low operation costs. The cost of a ride-hail will drop to $0.25 due to several factors.  Accidents per mile driven by autonomous vehicles are already lower than by human drivers, and with more autonomous vehicles on the roads, this will drop further. Autonomous vehicles drive in a more efficient way, also reducing fuel costs up to 44% for passenger vehicles and 18% for trucks.  

Autonomous Ride-Share Programs

Cruise

Cruise is a subsidiary of General Motors and became the first company to begin an autonomous ride-hailing service in a major city. In June 2022, Cruise received approval from the California Public Utilities Commission and started its public, driverless, fared, autonomous ride-hailing. 

Cruise launched with a fleet of 30 autonomous all-electric Chevy Bolts. These small cars ferry passengers around many parts of the city, and the service is currently available daily from 10 p.m. to 6 a.m. (provided “normal” weather conditions).

Source: Cruise

Cruise vehicles are limited to a maximum of 30 mph and cannot operate if there is heavy rain, fog, smoke, hail, sleet, or snow. Cruise is looking to add more Chevrolet Bolts to its fleet and increase the time it’s allowed to operate. 

Since 2020 Cruise has delivered a total of 2.2 million meals to San Francisco’s needy through a partnership with local food banks. Cruise has also begun the groundwork for autonomous ride-hailing services to launch in Dubai in 2023 and later in Japan.

Baidu

Chinese Technology giant Baidu began its Autonomous Driving Unit (ADU) in 2014 to design vehicles that could move passengers without the need for a driver. Baidu launched its “Apollo Go” self-driving robo-taxi business in 2017, and they recently upped the ante with their Baidu Apollo RT6 Autonomous Driving Vehicle in July 2022. 

In that same month, they received approval from the Beijing authorities to launch a robo-taxi service within a Beijing suburb. The new Apollo RT6 has a detachable steering wheel because the car no longer needs a driver. 

Source: Baidu

In August 2022, Baidu also obtained the permits to operate a fully autonomous taxi service in two Chinese megacities, Wuhan (11 million residents) and Chongqing (30 million residents). Baidu’s 100% autonomous robo-taxi services will begin on a small scale with a fleet of only five vehicles in each city and provide their service in designated areas from 9:30 a.m. to 4:30 p.m..  

Source: Baidu

Pony.ai

Pony has also received permits from Beijing authorities to provide their fair-charging, driverless robo-taxi service in July 2022. With this new permit, they are now able to charge fares for rides within a 60 square kilometer area (23.1 sq miles) in Beijing’s Yizhuang suburb. 

The service area includes public facilities like underground stations, parks, and sporting centers, as well as key residential and business districts. The new permit builds upon two other recent Beijing autonomous vehicle milestones. Pony.ai was allowed to launch a robo-taxi service with safety drivers in November 2021. 

Source: pony.ai

Since November 2021, Pony.ai has provided over 80,000 rides from 200 pickup or drop-off locations.  And by July 2022, their robo-taxi service called “PonyPilot+” completed a total of 900,000 orders with nearly 80% from repeat customers. Further, 99% of the passengers provided positive reviews once the trip was complete, with an average 4.9-star rating on a 5-point scale. 

Hyundai Motors

Korean automaker Hyundai launched is RoboRIde autonomous ride-hail service in Gangnam Seoul. The South Korean Land, Infrastructure, and Tourism Ministry issued Hyundai with permits to operate their autonomous vehicles in Seoul. 

The Seoul Metro Government established a system that connects traffic signals with autonomous vehicles. This system also supports autonomous vehicles with remote functions, such as lane changing under circumstances where fully autonomous driving is not feasible. 

Hyundai has been testing autonomous driving in Gangnam since 2019. The program so far includes only two self-driving IONIQ-5 vehicles, operating from Monday to Friday from 10 a.m. to 4 p.m. with up to three passengers. The program is slated to expand to the general public after successful tests. 

Source: SAE

Waymo One

The autonomous ride-hailing service from Alphabet (Google) started as the Google Car and has been running autonomous rides in the Phoenix metro area. It has recently expanded its program from the east valley suburbs, where it’s charging fares, to a new pilot program in central Phoenix. 

Both services run 24 hours a day, seven days a week. In their 2021 safety report, Waymo states that they have driven millions of miles on public roads in their ten years of service and, with simulations, have completed billions of driving miles.  

Source: Waymo

Closing Thoughts

As the number of autonomous vehicle ride-hailing projects increases, we will become increasingly used to the idea. The number of miles driven (both actual and virtual) will continue to grow, and as this happens, the insurance industry will begin to push toward autonomous driving. 

For the U.S.A. and other industrialized countries, the driving costs are high for human-driven vehicles. Economics alone will push for autonomy. The benefits of optimized fuel use and reduced traffic will continuously argue in favor of autonomous driving. We will soon all be passengers.

Disclaimer: The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment. Mr. Chalopin is Chairman of Deltec International Group, www.deltecbank.com.

The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business. Mr. Trehan is a Senior VP at Deltec International Group, www.deltecbank.com.

The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees.

How Digital Wallets Transform Banking

We have an economy that is switching to 5G, and in a few more years, we may see 6G speeds. However, the global economy’s digital transformation is far from complete. After our struggles with Covid-19 affecting both health and commerce, we have moved our world toward global, digital connectivity. For example, digital wallets will forever transform the way that we bank, shop and pay. 

Most of the world, including developed economies, is still only in the early stages of a true digital transformation. We will look at the future of digital wallets and see how they are going to be an integral part of the comprehensive digital potential that is coming to all of us. The new connected economy will be defined by several pillars, all affecting our daily lives. 

Digital Wallets

Digital wallets allow their owners to store and spend funds digitally in the form of “real” money linked to a debit, credit, gift card, coupons, or loyalty points. Digital wallets differ from other online payments because they allow the user to save payment information by adding their card or account information to the app. When payment is required, the buyer can do it straight from the app, only needing to hold the smartphone close to the reader, and not having to remember or enter payment credentials.

This is only the start of digital wallet capabilities. Digital wallets can do much more, from adding loyalty cards, airline boarding passes, movie tickets, hotel door keys, and more. The recent growth of this technology has allowed many to leave bulky wallets behind and has pushed our economy toward cashless payments. 

Apple, Samsung, and Google have all integrated these wallets into their devices and have become the biggest players in the space. Retailers like Walmart and Alibaba have added digital wallet capabilities to their checkouts, and PayPal, Cash App, and Venmo, which offer digital wallet services, have grown into financial powerhouses.  

Banking’s Future

Beyond the convenience digital wallets provide at checkout, they can potentially solve the cross-border banking problem, a difficult-to-navigate and disjointed process. Opening an international bank account is often long and painful, and international transfers can add more roadblocks and delays lasting days or more. 

New Fintech firms allow businesses to open their own international accounts with multicurrency IBAN in the organization’s name. Virtual wallets then make the process easier with same-day payments, while the company can keep funds in multiple currencies allowing for prompt payments and currency exchange.  

The Technology of Digital Wallets

Digital wallets start with a digital core. This is obviously the foundation behind the digital transformation of banking. And this digital core refers to the applications and platforms a financial institution utilizes in its transition to a digital business. 

It then uses open APIs (application programming interfaces) to integrate payment platforms and digital wallets, which bring front-end benefits to its consumers. With these fundamentals, institutions can build services that effectively and directly communicate to clients, driving transformational change. There are already many popular crypto wallets in Europe, Asia, and the Americas–nearly the whole world. 

Beyond the open APIs, we will see more smart ledgers and wallet management programs come forward.  These blockchain-based smart ledgers will transform the handling of digital wallets. Offering a way to record, transfer, and store alternative assets in token form, adding to digital wallet capabilities. When combined with API-accessible wallet management, users will experience a fully integrated digital payment model within a single platform. 

Crypto’s Potential

The rise of cryptocurrencies is still considered an untapped frontier of digital wallets. Trading these non-tangible digital currencies has increased, and the price of a bitcoin has risen from $1 in 2011 to tens of thousands today. Remaining speculative means that crypto is ripe for continued growth, and the push for CBDCs means that the banking sector is concerned. It’s even possible to use APIs for algorithmic trading.  

Visa is hedging its bet, building the structures for CBDC integration and for its own crypto digital wallet. This institutional interest and strong demand across wealth management are apparent, and there is a significant blockchain product offering that has the potential to transform the way markets behave. The blockchain value proposition has shifted to what else a blockchain can do beyond store value.  

Digital Wallets Connect Economies

In a report about the connected economy by Stripe and PYMNTS, which surveyed over 15,000 participants from 11 countries, the ongoing digital transformation has only reached about a quarter of its full potential across those studied. These 11 countries represent about 500 million adults, a small portion of our now 8 billion global population.  

Source: PAYMENTS

Brazil and other developing countries have massive potential to grow their connected stature. But even in highly connected places such as Spain, the UK, and Singapore, only about one-third of their digital connectedness has been achieved. The untapped potential hints that there are roadblocks to be overcome and transformation to be had. 

Streaming and Social Media

On average, the survey found that 87% of respondents were connected to the internet. However, fewer than 20% were highly engaged with digital activities, especially shopping. This is an interesting, ironic result of the slowing but persistent pandemic. However, streaming services are the exception. 

The research found that seven times as many consumers are engaged in watching streaming videos daily on YouTube, HBO or Netflix as are shopping on a marketplace like Amazon, Etsy, or eBay. Social media is the other plus point, with five times as many consumers checking their social media as compared to ordering food.   

Digital Wallet Use Is Here to Stay

Digital wallets are the key to this connected future. Covid-19 brought a growing embrace of touchless or contactless payments, speeding up digital wallet adoption. There is no clear digital wallet leader, and use patterns differ based on geography.

PayPal is commonly used in the most digital wallet-centric nation, Germany, accounting for 37% of all online transactions. More than 40% of all domestic online transactions in Germany are using digital wallets, with 84% of these using PayPal.

Sources: Stripe and PYMNTS

In 2019, mobile wallets surpassed credit card use globally, becoming the most widely used payment type.

Juniper Research predicts that the number of unique digital wallet users will grow from the current 2.6 billion to 4.4 billion by 2025. China and India will lead the way, accounting for nearly 70% of all digital wallet transactions, with the US and UK lagging in digital wallet adoption. 

Digital wallets have been successful in areas with low card penetration but high phone use. Southeast Asian consumers skipped cards, going from cash to mobile wallets, and digital wallet providers have done exceptionally well. 

With this adoption of digital wallets and newer forms of digital currency, cryptocurrencies or CBDCs will be in demand. Future digital wallets will seamlessly store and pay in several currencies, particularly as many retail online brokerages offer crypto and checking accounts. 

Closing Thoughts

As we become digitally connected, digital wallets play an obvious, necessary role. Their reach will spread, and governments and companies will push for their continued use. The increase in services they will supply, solving cross-border transaction issues, and improving the ease of banking will ensure that we use our digital wallets when we bank, shop, and pay. 

Other services should look to digital streaming and social media to see how we can better integrate digital payments and digital connectedness into our lives. China and India will continue to lead this march, but that doesn’t mean the West shouldn’t catch up quickly. 

Disclaimer: The information provided in this article is solely the author’s opinion and not investment advice – it is provided for educational purposes only. By using this, you agree that the information does not constitute any investment or financial instructions. Do conduct your own research and reach out to financial advisors before making any investment decisions.

The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment.  Mr. Chalopin is Chairman of Deltec International Group, www.deltecbank.com.

The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business.  Mr. Trehan is a Senior VP at Deltec International Group, www.deltecbank.com.

The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees.

AI in Agriculture 

Artificial intelligence, drones, and robots are already being deployed on large farms to assist with several farm management tasks for crops and livestock. However, there are some risks that must be accounted for when turning over our food production to AI-driven machines. 

We will discuss the benefits that AI can bring to the world of agriculture, including some applications that are already in place to help our farmers produce more and better-quality food. We will then discuss some potential pitfalls we must be aware of if we turn over our food supply to machines. 

AI’s Potential

AI has brought to the world countless tools for personal and industrial use. With agriculture, it has delivered the potential to increase yields, keep pests away, and reduce costs in nearly all parts of farm management. 

Our farmers need to know how best to use these tools, and we need to understand how their application can be a benefit. There are already AI applications that are worthwhile and are providing users with successful results. Let us see how the grass is greener on the AI side.

The Smart Farm

AI is leading to smart farms with farming models that have high cognitive ability.  This technology is focused on a few specific areas.

Data and Analysis

With new equipment, farms can be set up to track and analyze multiple data points. For example, a farmer can use a drone to review a large tract of land and identify the exact location of a pest infestation or plant disease in real-time. This mass of data has boosted information accuracy and can help farmers make informed decisions when analyzed with AI models.

Robotics and Automation

Robots are used for farm activities such as picking, thinning, and sorting to speed up manual labor work and deal with any labor shortages. The goal is to increase productivity, consistency, and quality while minimizing errors.

Predictions

AI models have been designed to predict changes to weather patterns, soil erosion, and pest infestations to improve farm management and planning. These tools allow farmers to see into the future, assisting them with informed decision-making.  

Like other industries, agriculture faces similar constraints related to its use of AI, such as compatibility with current technology, resource availability, security, and potential regulatory issues. Even with these constraints, the future farms will be highly dependent on AI, making them more precise and creating a new “cognitive farm.” 

Digital Farmers

AI is revolutionizing one of our oldest industries and giving farmers multiple ways to produce more abundant harvests in all parts of the world. With this transformation, farms will now require digital farmers, men and women, which can push forward these technological changes, managing future farms in new ways.  

Tools and People

New farm managers must understand and use the correct tools to their farm’s benefit. While extensive technical knowledge is not needed, understanding the basic principles behind the technology and, more importantly, the technology’s operational implications are necessary.  Through AI, farm managers can better understand the inner workings of their farms.

The changing technology means that farm talent must be updated. Beyond the typical farming roles, farms will require employees with technological skills. The entire organization will need defined education to stay on top of the AI farming future.  

New Ways of Farming

Farmers will need to leave their comfort zones and explore new collaborative opportunities. This change will involve collaboration with new companies to obtain cutting-edge technologies that will allow a farm to acquire a competitive advantage and boost productivity. These partnerships provide inimitable technologies, giving farmers the upper hand, but these technologies work best for large farms.  

Cost advantages are most significant with economies of scale.  So, managers will benefit by finding strength in numbers.  AI tools can be expensive, beyond the reach of the small farm.  When collaborating with other farms, cooperatives, suppliers, universities, local communities, and the government, these costs can be driven down. 

AI’s Current Applications

AI currently monitors soil, detects pests, determines diseases, and applies intelligent spraying. Here are a few of the current applications farmers are already using today. 

Crop Monitoring

Crop health relies on micro and macronutrients in the soil to produce yields but with quantity and quality. Once the crops are planted, monitoring their growth to optimize production is also needed. Understanding the interaction between growth and the environment is vital to adjust for healthy crops. Traditionally this was done through human observation and experience, but this method is neither accurate nor speedy. 

Now drones capture aerial data, then train computer models to intelligently monitor crops and soil. This AI system can use the collected data to:

  • Track the health of the crops
  • Accurately predict yields
  • Identify crop malnutrition

This can all be done faster than a human could, in real-time, providing farmers with specific problem areas so they can take immediate actions to prevent problems before they grow.  

Determining Crop Maturity

Wheat head growth is a labor-intensive process that can be aided with AI. Over a three-year period, researchers collected wheat head images at different stages with different lighting, building a two-step wheat ear detection system. The AI model was able to outperform human observation, allowing farmers not to have to make daily visits to fields to check on the crops.  

Similarly, tomato ripeness has been determined with AI. 

A different study examined how well AI can detect maturity in tomatoes.  The researchers built a model looking at the color of five different parts of a tomato, then made maturity estimates.  The algorithm could correctly classify tomatoes with a 99.31% accuracy. 

Generally, evaluating soil involves digging up samples and sending them to the lab for analysis. AI researchers have used image data from a cheap microscope to train their model to do the same task. The model was able to make sand content and soil organic matter estimates with accuracy similar to costly and slower lab analyses. 

Disease and Insect Detection

Using deep learning, farmers are now automating the detection of plant diseases and pests.  This is done through image classification and segmentation. 

Source: V7 labs

A study looked at the apple black rot and used a deep neural network AI model to identify the four stages of disease severity. Like with the other models above, the disease identification process is labor-intensive. This project was able to identify the disease severity at an accuracy of 90.4%.  

Similarly, a different study was able to use the YOLO v3 algorithm and was able to identify multiple pests and diseases on tomato plants. Using only a digital camera and smartphone, researchers identified twelve different cases of disease or pests. Once trained, it was able to detect problems with an accuracy of 92.39%, taking only 20.39 milliseconds. 

Source: Frontiers In

Another study used sticky traps to collect six flying insects and collect images. They then based the course counting on object detection and fine-counting results. The model identified bees, mosquitoes, moths, flies, chafers, and fruit flies with a 90.18% accuracy and a 92.5% counting accuracy.  

Livestock Monitoring

Animals are a major component of our food system and need even more tracking than plants.  Companies are now offering tools to track cattle and chickens. CattleEye tracks and annotates key points for individual cows. 

Source: CattleEye

The system uses overhead cameras to monitor animal health and behavior, allowing a rancher to spot a problem and be notified without being next to the cow.  

By collecting data with cameras and drones, this kind of software is being used to count animals, detect disease, monitor birthing, and identify unusual behavior. It also confirms access to food and water. 

Smart Spraying

AI also prevents problems in the first place. Drones help with the spraying of fertilizer and pesticides uniformly across a field. They operate with high precision in real-time, spraying correctly and reducing contamination risk to animals, humans, and water resources.  

This is a growing field and is best performed by multiple drones, but intelligent spraying is getting better. Virginia Tech researchers developed a smart spray system that can detect weeds. 

A camera mounted on a sprayer records the geolocation of the weeds, analyzing their size, shape, and color, and then delivers a precise amount of herbicide. 

Source: Researchgate

The device’s accuracy prevents collateral damage to other crops in the environment.  

Risks of AI in Agriculture

All these different AI applications will help us monitor and improve our food systems, helping feed the 2.4 billion people suffering from food insecurity. AI can reduce labor inefficiency and increase reliability. However, there are some cautionary tales. 

According to a release by Asaf Tzachor of Cambridge University, there could be flaws in the agricultural data, emphasizing productivity over environmental concern. This focus could lead to errors that cause over-fertilization and pesticide use, improper irrigation, and soil erosion.  These factors must also be considered when designing AI systems. Inadvertent changes resulting in crop failures could result in massive food insecurity.  

Cybersecurity is a second issue. Cyberattacks could disrupt entire food systems, especially for farms that rely heavily on AI.

Finally, those without access to the new technology could be cut out of markets. Big farmers will profit, and small farms will be locked out of the gains entirely if they cannot afford the AI infrastructure. 

Planning Ahead

As in all enterprises, diligence and conscientious planning contribute to farming success.  Farmers must plan their AI strategy by optimizing their operations and yield requires thoughtful assessment. This planning involves a thorough review of priorities and a clear implementation plan.  

AI provides tools that can boost a farm’s yields, and transform the industry. Increases in agricultural production on a large scale will impact a country’s GDP, increase food security, and positively impact the environment. The US had just over two million farms in 2021, averaging 445 acres each, totaling 89.5 million across the country.  

Analytics and robotics boosts production on almost any farm. AI-related productivity gains can reshape the farming business and improve our global food supply. This is a way we can counteract the climate factors that could affect corn, rice, soy, and wheat production by 20-49%.

Closing Thoughts

Since the advent of agriculture, technology has improved its efficiency. From plows and irrigation to tractors and AI, we have moved forward to feed our growing population. With the ongoing changes to our climate, AI has arrived just in time to save us all from potential food insecurity. We must use AI to increase efficiency and reduce food production costs while also improving environmental sustainability. Doing so can make our farmers “smarter” and give us more and healthier foods.  

If small farmers can work together and take full advantage of these new AI tools, they can compete with large industrial farms. We also have to ensure that the systems that are put into place are safe and have an all-encompassing view that does not only focus on yields but the potential environmental effects. Sustainability remains crucial, and AI is the missing piece. 

Disclaimer: The information provided in this article is solely the author’s opinion and not investment advice – it is provided for educational purposes only. By using this, you agree that the information does not constitute any investment or financial instructions. Do conduct your own research and reach out to financial advisors before making any investment decisions.

The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment.  Mr. Chalopin is Chairman of Deltec International Group, www.deltecbank.com.

The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business.  Mr. Trehan is a Senior VP at Deltec International Group, www.deltecbank.com.

The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees.

Spotting Deepfakes

A deepfake is a piece of image, audio, or video content using artificial intelligence to create a digital representation by replacing the likeness of one person with another. This advanced technology is becoming more common and convincing, leading to misleading news and counterfeit videos. 

We will delve deeper into deepfakes, discuss how deepfakes are created, why there are concerns about their growing prevalence, and how best to detect them so as not to be fooled into believing their content.  

Rise of the Machines

Advances in computers have allowed them to become increasingly better at simulating reality. What was once done taking days in the darkroom can be done in seconds using photoshop. For example, five pictures of the Cottingley Fairies tricked the world in 1917.  

Modern cinema now relies on computer-generated characters, scenery, and sets, replacing the far-flung locations and time-consuming prop-making that were once an industry staple.  

Source: The Things

The quality has become so good that many cannot distinguish between CGI and reality.

Deepfakes are the latest iteration in computer imagery, created using specific artificial technology techniques that were once very advanced but are beginning to enter the consumer space and will soon be accessible to all.  

What Are Deepfakes?

The term deepfake was coined from the underlying technology behind them, deep learning, a specific field of Artificial Intelligence (AI) or machine learning. Deep learning algorithms have the ability to teach themselves how to solve problems better, and this ability improves the more extensive the training data set provided to them. Their application to deepfakes makes them capable of swapping faces in video and other digital media, allowing for realistic looking but 100% fake media to be produced.  

While many methods can be applied to create deepfakes, the most common is through the use of deep neural networks (DNNs). These DNNs use autoencoders that incorporate a face-swapping technique. The process starts with a target video that is used as the basis of the deepfake (on the left above) and from there, a collection of video clips of the person (Tom Cruise) that you wish to overlay into each frame of the target video.

The target video and the clips used to produce the deepfake can be completely unrelated. The target could be a sports scene or a Hollywood feature, and the person’s videos to insert could be a collection of random YouTube clips.

The deep learning autoencoder is an artificial intelligence program tasked with selecting YouTube clips to understand how the person looks from several angles, accounting for different facial patterns and environmental conditions. It will then map that person into each target video frame to make it look original. 

An additional machine learning technique called Generative Adversarial Networks or GANs is added to the mix, which detects any flaws and improves the deepfake through multiple iterations. GANs are themselves another method used to create deepfakes. They rely on large amounts of data to learn how to create new examples that mimic the real target. With sufficient data, they can produce incredibly accurate fakes.  

Deepfake Apps

Deepfake apps have also hit the consumer market, such as Zao, FaceApp, DeepFace Lab, Face Swap, and the notorious and removed DeepNude–a particularly dangerous app that generated fake nude images of women.

Several other versions of deepfake software that have varying levels of results can be found on the software development open-source community GitHub. Some of these apps can be used purely for entertainment purposes. However, others are much more likely to be maliciously exploited.

How Are Deepfakes Being Used?

While the ability to swap faces quickly and automatically with an app and create a credible video has some interesting benign applications, in Instagram posts and movie production, deepfakes are obviously dangerous. Sadly, one of the first real-world deepfake applications was in the creation of synthetic pornography. 

Revenge Porn

2017 saw a Reddit user named “deepfakes” create a forum for porn featuring face-swapped actors.  Since then, the genre of “revenge porn” has repeatedly made the news. These deepfake use cases have severely damaged the reputations of celebrities, prominent figures, and even regular people.  According to a 2019 Deeptrace report, pornography constituted 96% of deepfake videos found online, and this has only dropped to 95% in 2022.  

Political Manipulation

Deepfakes have already been employed in political manipulation. Starting in 2018, for example, a Belgian political party released a video of, at the time, President Donald Trump giving a speech that called on Belgium to withdraw from the Paris climate agreement. The former president Trump never gave that speech. It was a deepfake. 

The Trump video was far from the first deepfake created to mislead, and many tech-savvy political experts are bracing for the future wave of fake news featuring convincingly realistic deepfakes. We have been fortunate not to have so many of them during the 2022 midterms, but 2024 may be a different story. They have, however, been used this year to change the course of the war in Ukraine.  

Non-Video Deepfakes

Just as deepfake videos have taken off, their audio counterparts have also become a growing field with many applications. Realistic deepfake audio can be created with similar deep learning algorithms using samples of a few hours of the target voice. 

Once the model voice has been created, that person can say anything, such as the audio deepfake of Joe Rogan. This method has already been used to perpetrate fraud, and will likely be used again for other nefarious actions.

There are beneficial uses for this technology. It could be used as a form of voice replacement in medical applications, as well as in specific entertainment situations. If an actor was to die before the completion of the movie or before a sequel is started, their voice could be fabricated to complete lines that were not yet spoken. Game programmers can make characters who can say anything in real-time with the real voice rather than using a limited script recorded by the voice actor.  

Detecting Deepfakes

With deepfakes becoming ever more common, our society must collectively adapt to the spotting of deepfake videos in the same way that we have become attuned to detecting various kinds of fake news online. 

As is the case with all types of cyber security, there is a cat-and-mouse game where a new deepfake technology must emerge before a relevant countermeasure is created. This process is a vicious cycle, like with computer viruses, which is an ongoing challenge to avoiding the harm that can be done.

Deepfake Indicators

There are a few tell-tale giveaways that help in spotting a deepfake.

The earlier generation of deepfakes were not very good at animating faces, and the resulting video felt unnatural and obvious. However, after the University of Albany released its blinking abnormality research, newer deepfakes have incorporated natural blinking into their software–eliminating this problem.

Second, look for unnatural lighting. The deep fake’s algorithm will often retain the illumination of the provided clips that were used to create the fake video’s model. This results in a lighting mismatch. 

Unless the audio is also created with a deep fake audio component, it also might not match the speech pattern of the person that is the target. The video and the audio may look out of sync unless both have been painstakingly manipulated.  

Fighting Deepfakes Using Technology

Even though the quality of deepfakes continues to improve and appear more realistic with technical innovation, we are not defenseless to them. 

Sensity, a company that helps verify IDs for KYC applications, has a deepfake detection platform that resembles an antivirus alert system.  

The user is alerted when they are viewing content that has signs of AI-generated media. Sensity’s system uses the same deep learning software to detect as is used to create the deepfake videos.  

Operation Minerva uses a more straightforward approach to identifying and combating deepfakes.  They employ a method of digital fingerprinting and content identification to locate videos made without the target’s consent. It can identify examples of deepfakes, including revenge porn, and if identified, it will send a takedown notice to sites that Operation Minerva polices. 

There was also a Deepfake Detection Challenge by Kaggle, sponsored by AWS, Facebook, Microsoft, and the Partnership on AI’s Media Integrity Steering Committee. This challenge was an open, collaborative initiative to build new ways of detecting deepfakes. The prizes ranged up to a half million dollars.  

Closing Thoughts

The advent of deepfakes has made the unreal seem real. The quality of deepfakes is improving and combating them will be more problematic as the technology evolves. 

We must remain diligent in finding these synthetic clips that can seem so real. They have their place if used for beneficial reasons, such as in entertainment and gaming, or med-tech to help people regain speech. However, the damage they can do on personal, financial, and even social levels has the potential to be catastrophic. Responsible innovation is vital to lasting success.

Disclaimer: The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment. Mr. Chalopin is Chairman of Deltec International Group, www.deltecbank.com.

The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business. Mr. Trehan is a Senior VP at Deltec International Group, www.deltecbank.com.

The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees.

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