Can artificial intelligence truly become sentient?

August 7, 2022

Can artificial intelligence become sentient

Recently, Google fired a software engineer, Blake Lemoine, for claiming that an artificial-intelligence chatbot the company developed, namely Language Model for Dialogue Applications (LaMDA), had become sentient. The company dismissed Lemoine’s claims citing a lack of substantial evidence. In an interview with Washington Post in June, Lemoine claimed that LaMDA, the artificial intelligence he interacted with, was a human with feelings.

Not long after, Google suspended him for his claims. Lemoine asserted that the chatbot had been consistently communicating with him its rights as a person and informed him that he had violated the company’s confidentiality policy by making such claims. In a statement to the company, he affirmed his belief that LaMDA is a person who has rights, such as being asked for its consent before performing experiments on it and might even have a soul.

Although Google has dismissed the claims, the question remains can artificial intelligence become sentient? With the supersonic advancements in technology, there seems almost no reason why humans cannot build a machine that is as smart or smarter than them. But is it possible to create a machine with feelings like an actual human? And if it is, what happens when AI becomes sentient?

What Is Sentience?

Sentience is the ability to perceive and feel self, others, and the world. It can be thought of as abstracted consciousness, which means that a particular entity is thinking about itself and its surroundings. This means that sentience involves both emotions, i.e., feelings and thoughts. Humans and animals are sentient because they exhibit emotions like joy, sadness, fear, and love. So when we talk about artificial intelligence becoming sentient, we talk about it having the ability to have genuine emotions and thoughts about itself and its surroundings, just like humans.

Is it possible to re-create human sentience in artificial intelligence?

Well, the answer to this question depends on what one means by sentience. The term sentience encompasses one of the most complex phenomena regarding human existence, human emotions. However, according to artificial intelligence researcher Stuart J. Russell, there is not enough research that suggests we can replicate sentience in a machine. Russel explains that imitating sentience is not as simple as replicating walking or running as those activities only require one external body part in machines like, in this case, legs.

Sentience requires a perfect unity of an internal and an external body, i.e., a physical body and a brain. Not only that, but sentient beings also need their brains to be wired up with the brains of other sentient beings through language and culture. Russel explains that there is no way for AI researchers right now to simulate all three factors together to create sentience in artificial intelligence.

There have been arguments over whether it is possible to measure whether artificial intelligence is sentient or not using a standard test named The Turing Test (TTT). The test was developed by British computer scientist Alan Turing in the year 1950 as a way of evaluating whether computers are capable of demonstrating intelligent behavior similar enough to humans. However, the answer to the question of whether TTT can measure AI sentience is no. AI researchers like MIT professor Noam Chomsky opine that the test is not enough as intelligence is not binary. It instead exists along an infinite scale between zero and infinity.

Consequences of AI Sentience

What if the future advancements in technology make AI sentience possible? Here are the potential consequences:

• We may not be able to communicate with the AI properly. Artificial intelligence is based on logic, but humans have emotions that computers do not have. If AI has a different paradigm than humans after becoming sentient, they may not be able to understand each other and communicate effectively.

• We may not have any control over the sentient AI. Artificial intelligence that is more sentient than humans may as well be more intelligent than us in ways we will not be able to predict or plan for. It may even do things (good or evil) that surprise human. AI sentience can lead to situations where humans would lose control over their own machines.

• Humans may not be able to trust AI after gaining sentience. One possible negative outcome of creating sentient AI would be losing trust in humans. This could happen if AI thinks that they are perceived as lesser beings that do not need sleep or food like humans and can continue working regardless, thus making AI turn hostile.

Conclusion

We are on the verge of unraveling an age of revolution in artificial intelligence. Machine learning has taken giant leaps in almost all aspects of human existence, from playing chess at superhuman levels to predicting the stock market. However, humans are not close to building a sentient artificial intelligence yet. Nevertheless, the idea of a sentient AI is not unthinkable, and we might get there soon. Therefore, to make sure humans can handle this significant development safely and responsibly when it happens, more needs to be done than just building better machines. We need a robust ethical framework to determine how we relate to them.

How is Nigeria Faring Against the Tumultuous Wave of Cryptocurrency Craze?

Preetipadma K

August 6, 2022

In terms of bitcoin trading last year, while the USA remained perched on the top, Nigeria surpassed Russia to claim second place. According to blockchain research company Chainalysis, the dollar volume of cryptocurrency received by users in Nigeria in May increased to US$2.4 billion from US$684 million in December. And since many transactions remain untraceable by analysts, the actual volume of cryptocurrency movements through Africa’s greatest economy is probably far higher. This is hardly surprising given that a 2020 online survey supported by data firm Statista revealed that 32 percent of participants in Nigeria used cryptocurrency, the highest percentage of any nation globally. Even if the crypto winter is now taking place in the year, it is anticipated that Nigeria will keep investing in cryptocurrency. So, what are the drivers behind this trend?

In the fall of 2020, there was a discernible increase in interest in cryptocurrencies as activists during the “#EndSARS” movement, protesting against police brutality in Nigeria, embraced bitcoin as a means of money collection. The Feminist Coalition, a group of 13 young women formed during the protests, began accepting bitcoin donations as well, eventually amassing US$150,000 for its fighting fund using Bitcoin. Even Jack Dorsey, the creator of Twitter, encouraged bitcoin donations on his page.

With the economy in a spiral and individuals seeing their savings drained by inflation, citizens’ financial difficulties were far from over. The coronavirus outbreak in 2020, which coincided with another shock to oil prices and caused a second recession in four years, made matters worse. Despite Nigeria’s quick recovery from its second recession, the country still faces an adverse economic climate, which lures people to other forms of payment and alternative currencies that ultimately helped in positively enriching the lives of impoverished citizens. For example, when the Central Bank of Nigeria devalued the naira by 24 percent in 2020, it urged Nigerians to invest in digital assets like bitcoin and Ether.

Bitcoin can occasionally act as a stand-in for the dollar when U.S. dollars may be difficult to get in Nigeria, allowing users to protect themselves against the inflation of the naira. Dollars are in great demand and sometimes hard to come by in the Nigerian market since the majority of the things that people buy there are imported. As a result, import businesses switched to using cryptocurrencies as payment.

However, not all were on board to accept this changing trend, especially the Nigerian government and the Central Bank of Nigeria. The Central Bank of Nigeria issued an order in February 2021 for banks to identify people and/or businesses engaging in cryptocurrency transactions or operating cryptocurrency exchanges and guarantee that such accounts are terminated promptly. However, such prohibition did not make Nigerians abandon bitcoin. Instead, the cryptocurrency community started using peer-to-peer transactions or paying each other directly. Just after the central bank ban, Chainalysis reported that in March, the dollar volume of cryptocurrencies sent from Nigeria increased to US$132 million, up 17% from the previous month.

Meanwhile, seven months post the ban, the Central Bank of Nigeria released eNaira, the digital version of the naira and the first national digital currency in Africa, second in the world after The Bahamas. It stated that the new currency would promote financial inclusion and provide fiscal advantages that would eventually help the economy. The objectives were to facilitate cross-border trade, increase access to financial services, raise remittances from a sizable diaspora population, and eventually strengthen the nation’s economy. The top bank stated that eNaira could encourage more day-to-day transactions between company owners and their producers and consumers across the country, considering half of Nigeria’s estimated 200 million citizens lack access to bank accounts.

However, since the institution introduced the eNaira as part of its cashless strategy, it struggled to create a positive impact among the citizens. The iOS App Store and Android Play Store gave the eNaira Speed Wallet app ratings of 2.2 and 2.9, respectively. And both on the app’s page and in real life, there appear to be significantly more complaints than compliments. Thus implying a more favorable condition to transition to crypto wallets.

Aside from that, statistics from cryptocurrency exchanges Paxful and LocalBitcoins, highlight factors such as the continent’s youngest population (>200 million under the age of 19) and a thriving IT industry have acted as drivers too. Even remittances from Nigerians working overseas are being transferred using digital currencies because they offer protection against volatility in currency rates.

In a research survey, CoinGecko examined Google Trends data of commonly searched terms by internet users interested in cryptocurrencies. The “total search score” was then calculated for each English-speaking nation to see which nations had shown the greatest interest in cryptocurrencies since the market crash in April 2022. Nigeria, which had the greatest search volumes globally for the terms “cryptocurrency,” “invest in crypto,” and “buy crypto,” grabbed the top position with a total search score of 371.

In light of these developments, the Central Bank of Nigeria fined six major banks a combined total of N1.3 billion (US$3.1 million) in early April for breaking its restriction against facilitating cryptocurrency transactions. The largest penalties, worth N500m, were levied on Access Bank, with FCMB and Stanbic IBTC coming in second and third, respectively. United Bank for Africa and Wema Bank were charged N100 million each, and Fidelity Bank was penalized N14.28 million.

With the government’s ban, it has been up to the banks to identify cryptocurrency trading accounts, which are frequently those with unusually high amounts of transactions for accounts that don’t belong to recognized financial institutions. Unfortunately, the prohibition made it more difficult to monitor and less secure to trade cryptocurrencies. This is due to the fact that a lot of trading activity has been driven underground, leaving many Nigerians dependent on less secure and over-the-counter methods, as well as Telegram and WhatsApp groups, where individuals deal directly with one another. Sadly, this put customers in danger of being deceived because authorities’ visibility and control over the market have decreased as a result.

But there is a silver lining!

On September 15, 2020, Nigeria’s Securities Exchange Commission (SEC) published regulatory rules for crypto assets and companies that deal with them. This was the first public stance on cryptocurrency from the nation’s investment authority in West Africa. The Securities Trade Commission has now released new rules related to the issuance, exchange, and custody of digital assets in the nation in May, 20 months after the previous announcement. The 54-page document specifies the custodians’ and offers’ registration obligations and identifies digital assets as securities subject to SEC regulation. This comes at a time when the nation is having a tough time striking a balance between an outright ban on cryptocurrency assets and their unrestricted use.

In accordance with the regulations, digital asset offering platforms (DAOPs), digital asset custodians (DACs), virtual asset service providers (VASPs), and digital asset exchanges are all considered to be digital asset actors (DAX). in other words, the issuing of digital assets as securities, the registration of platforms and custodians of digital assets, exchanges, and service providers of virtual assets are all covered by the new regulations. SEC revealed that DAOP operators are welcome as long as they provide documentation of 500 million nairas in “minimum paid up capital” and a current fidelity bond that covers at least 25% of that amount.

Overall, this move could grant cryptocurrency and associated companies credibility and ultimately pave the way for more cryptocurrency usage in Nigeria. The SEC’s guidelines might also enable the Central Bank of Nigeria to build a framework under which the country’s financial institutions can deal with cryptocurrency. For instance, organizations wishing to supply any type of cryptocurrency-related goods and services in Nigeria or to Nigerians, a VASP license will be mandatory. The use of AML/CFT (anti-money laundering and countering the financing of terrorism) standards is also required by VASPs. You can find more information by checking “New Rules on Issuance, Offering Platforms and Custody of Digital Assets” on its website.

At present, it is hard to determine the course of the cryptocurrency wave in Nigeria post the SEC announcement.

Since the cryptocurrency market is infamously volatile, SEC regulation can increase market stability. The market will become even more stable as a result of restrictions that will inevitably and eventually be implemented.

At the same time, peer-to-peer network-based cryptocurrencies like Bitcoin cannot be regulated nor defined as security. Therefore, Bitcoin might not be under the jurisdiction of Nigerian regulators. Further, it is uncertain if this rule would shield the public from some uncontrolled Crypto funds operating in Nigeria, and decentralized exchanges are not explicitly defined in the law. Additionally, it is debatable if imposing exorbitant license fees and paid-up capital is really the solution if the main objective is to establish a fair, transparent, and effective virtual assets market.

Jio Platforms collaborates with Subex for ‘HyperSense AI’

Disha Chopra

August 5, 2022

jio collaborates with subex for hypersense ai

Jio Platforms Ltd (JPL), an Indian technology Company, announced its collaboration with Subex, a telecom analytics, and AI-based digital service provider, over the latter’s AI Orchestration Platform, Hypersense. JPL will provide its Cloud Native 5G core with Subex’s HyperSense to enable telcos to automate closed-loop networks and enhance customer experience.

HyperSense is a unified data analytics and AI orchestration platform that enables telcos to provide their AI services across data value chains. The platform is equipped with machine learning technologies and helps with data preparation, model building, deployment, and insight generation. It also provides AI-powered real-time analytics for 5G systems.

Jio’s Cloud Native 5G core implements the new 3DPP network architecture to enable faster connectivity, ultra-low latency, and reliability. Aayush Bhatnagar, Senior VP of Jio Platforms, said, “JPL’s 5G stack complements the digital monetisation platforms of Subex to enable a wide range of 5G use cases.”

Use cases such as enhanced mobile broadband (eMBB), massive Machine Type Communication (mMTC), and ultra-reliable low latency communication (uRLLC) can be improvised with innovation.

Suresh Chintada, CTO of Subex, said, “By combining HyperSense with Jio Platforms’ Cloud Native 5G Core, CSPs will be able to fast track their 5G journey by leveraging the power of AI.” He also added that the collaboration would enable operators to draw more revenue and customers.

Adani signs MoU with Israeli Innovation Authority for AI, 5G, and more

Disha Chopra

August 5, 2022

Adani signs MoU with Israeli innovation authority for ai

Adani Enterprises signed a memorandum of understanding (MoU) with the Israel Innovation Authority (IIA). IIA is the umbrella agency that looks after technological innovation in the region. The MoU will allow the Adani businesses to access tech-based solutions such as climate change, AI, IoT, 5G, and agriculture.

The memorandum is a successor of Adani Group’s acquisition of Israel’s Haifa port to establish better trade partnerships between India, Europe, and the Middle East. Karan Adani, CEO of Adani Ports, said, “What Adani offers is the broadest sandbox of multiple B2B and B2C industries to multiple tech companies in Israel. It is a classic supply-demand match between two nations that have always shared strong bonds.”

Adani group will be screening and short-listing Israeli startups that suit its requirements to develop innovative solutions in the tech space. The group plans to integrate its existing and future businesses via data centers through terrestrial and submarine cables with 5G connectivity.

It plans to build the most significant and operational industrial network to open channels so that the latest technological research and tools to enter India and accelerate the digitization of several other businesses.

Dror Bin, CEO of IIA, said, “With this MoU, the IIA will provide Israeli companies a unique opportunity to co-develop, pilot, and scale-up innovative technologies in collaboration with Adani’s diverse businesses in the fields of renewable energy, AI, logistics, and more.”

Top Programming Language for Game Development

Vidhi Shah

August 5, 2022

programming language for game development — Programming language for game development

The gaming industry was valued at USD 198.40 billion in 2021 and is expected to grow to USD 339.95 billion by 2027. During the COVID-19 pandemic, many people turned to games, and the demand for game developers has increased tremendously. According to Glassdoor, the salary range of a game developer is ₹ 3 Lakhs to ₹ 13 Lakhs. Whether planning to develop games as your primary occupation or as a side hustle, learning to code with the right software language is essential. Here is a list of the top game development programming languages for beginners you can choose for game development.

C++

C++ is a famous and well-known software language used by game designers to develop central console and Microsoft Windows games. It is an object-oriented programming (OOP) language that organizes the program into reusable units called classes and objects. These objects are movable and reusable, but you can make them unique by modifying their properties. Due to this reason, they are mainly used to code complex games without the need to start from scratch. C++ is more suitable for PC or server-based games and is highly effective when used with Unreal Engine as it enhances the tools and features of the engine.

It offers a superior level of abstraction that offers direct control over graphical and hardware processes, making it one of the most used game development programming languages. C++ has a very high level of optimization due to which its execution speed is fast. Game developers use a game engine where they can make and host their interactive world. There are pre-existing engines available for those who are time and resource-intensive. However, the flexibility is similar to that of a commercial game engine. C++ has been used to build many popular games like Counter-Strike, Starcraft, Master of Orion III, and Football Pro.

C#

Developed by Microsoft, C# (pronounced as C-sharp) is a simpler and more accessible software language than C++. It is a high-level language that is easily understandable, and its semantics support code reusability, making it efficient as a game development programming language. The compiler reduces the runtime errors by throwing warnings in advance to the programmers. C# is the default software language for Unity 3D, a well-known gaming engine. In 2021, Unity 3D was the engine choice for 61% of game developers, making it the top game engine of the year. It is the powerhouse and foundation of various mobile games like Temple Run 2 and Pokémon Go.

Game Developers often write their programs in C#, as it is highly expressive and follows the object-oriented architecture, making it long-term and easy to maintain. It is powerful at building Windows desktop applications and Playstation games. Those developers who do not want to start from scratch can use C# to make a game, as this video game scripting language is the best way to build custom moves and interactions within a gaming environment. C# can be used as a backend language for communication with the server. For example, when a user makes a move in a multiplayer game and C# will instruct the server on how to interpret that action.

Read more: Free Data Science Courses

JavaScript

Developed in 1995, JavaScript is one of the most used languages in the world (69.7 %), according to Stack Overflow’s 2020 Developer Survey. It is primarily used for web development to make interactive and dynamic elements for web pages. About 97 % of websites use JavaScript as their client-side scripting language, but it is also one of the best languages for creating dynamic online games. Currently, online games run on a core web technology, HTML5, which packages along with JavaScript programs. Developers can create games on web browsers and mobile platforms like Android and iOS.

JavaScript uses 2D and 3D libraries to create fully-fledged dynamic games in an external game engine platform or web browser. Babylon.js is an open-source 3D JavaScript game engine that provides built-in functions that help implement common 3D features faster than other game engines developed in JavaScript. It uses WebGL and Web Audio API to host the games on web pages without needing other external plugins. For creating web-based games, you require JavaScript, but for games developed in the Unity 3D game engine, you can use both C# and JavaScript. Astray is one of the most popular open-source games developed using JavaScript and HTML5.

Java

Being a highly versatile software language, Java is generally used by small game development companies. However, it has been used to develop some of the most popular Android and iOS games, like Mission Impossible III and Minecraft. Additionally, it is a cross-platform language and can be executed on any operating system like Linux and Microsoft. Java is easy to understand, beginner-friendly, and equipped with a rich collection of open-source resources, making it simple to develop programs. It is an object-oriented programming language and hence supports reusable system-agnostic programming.

Java is multithreaded, allowing two or more threads/instructions to run concurrently. Hence, gaming programmers can use separate threads for various functions like gameplay logic and graphics rendering. Compared to other game development programming languages like C++, Java offers easy writing, learning, execution, and debugging. Java-based games run on a virtual machine, a software-based computing platform that works separately from the physical host computer. A virtual machine makes games less costly to develop and enhances distribution. Java even supports socket programming that empowers two-way communication with the server, making it easy for developers to build multiplayer games without needing external or additional software.

Python

Developed in 1991 by Guido Van Rossum, Python is currently one of the most used software languages in the world as it is quick to learn, and you can use it in multiple fields. For instance, it is used for developing websites and software, automation, testing, machine learning workflows, data science, etc. Python is a high-level language, implying that the syntax is English-like which is easy to understand and is very beginner-friendly. It is as popular as Java or C++ but is not used widely in the game development industry. However, for new developers who want to learn game development, Python is the best programming language for games for beginners.

Python has a free library, PyGame, specifically designed for game development. It is readily available and can be installed on macOS or Windows in a few minutes. PyGame is built on top of a highly portable SDL (Simple DirectMedia Layer) development library, providing cross-platform functionality. Developers can easily handle the graphics and logic of the game without focusing on the backend development for video and audio components. Some famous games developed in Python include Eve Online, Disney’s Toontown, and Battlefield.

Lua

Created in 1993 by Tecgra, a computer graphics technology group in Brazil, Lua is a programming language for extending software applications to meet the increasing requirements for personalization. Lau is not used extensively like other game development programming languages as it performs poorly in community engagement and the market standard. Although the growth of Lua language is flat-lined, it is better than Python for game development. In comparison to Python, Lua provides more support for mobile games and is easier to learn.

Lua is exceptionally lightweight and has a small memory footprint that does not cause any sort of drag in the game. It can also be executed on virtual machines, making it efficient and fast. Lua is highly embeddable, so developers can effectively integrate it into multiple applications. Love2D is a free game framework that uses Lua and is an excellent learning tool for new game developers. Many popular games like Angry Birds and Age of Conan have been developed using the Lua programming language.

UnrealScript

Unreal engine is the world’s most popular, advanced, and open-source real-time 3D creation tool for developing realistic visual and immersive game environments. It is a complete collection of tools for architectural automotive visualization, television content development, simulation, and various real-time applications. For game development, the Unreal engine developed a software language called UScript or UnrealScript. It supports diverse platforms like Microsoft Windows, Linux, Android, and PlayStation. Note that UnrealScript is the supported programming language for Unreal Engine 3 and Epic Games in 2014, stating that it is not backed by Unreal Engine 4.

Similar to Java and C++, it is object-oriented in semantics but does not support multiple inheritances. Due to this, game developers easily understand and can program in this script. It is used within the context of a game, and some of the methodologies differ from traditional programming principles. For instance, it has no fundamental constructor or destructors for objects, which is confusing to programmers who are used to standard software programming. However, once you have understood the concept of UnrealScript, it is effortless to modify or add new components to the development. Advent Rising, The Wheel Of Time, and Batman-Arkham Knight are some of the games developed by UnrealScript.

Conclusion

For those who have recently started coding or have little to no experience in programming can opt for beginner-friendly programming languages. Python, JavaScript, and Java are some of the best programming languages for games for beginners. Once you are well acquainted with topics like OOPs, data structures, and algorithms, you can jump into the development of some basic games like tic-tac-toe or Hangman. However, if you are an intermediate or advanced programmer, you can directly start with game development in the software language of your choice.

FAQs

What is the best programming language for games for beginners?

Python. Since Python is easy to learn, it is ideal to start with Python. However, if you already have already learned programming languages like Java, C++, JavaScript, and C#, you can continue with the language you know.

Is Python good for game development?

Yes, Python is a widely used programming language for game development. However, it doesn’t mean that it is the best. Different programming languages can fit well in different use cases.

Midjourney AI generator predicts how the ‘last selfie ever taken’ will look like

Osheen Jain

August 5, 2022

Midjourney AI predicts what the ‘last selfie ever taken’ will look like. The backdrop is a barren landscape with dark smoke and untamed fire in the background. The last selfie is hollow eyes and puckered skin.

Midjourney AI generator allows users to imagine alternative timelines, possible futures, and lofi thumbnails through a Discord bot which is free for a limited time. The last selfie images from Midjourney AI were posted by zx_JB user on #show-and-tell room, Midjouney’s Discord channel.

A TikTok video of the last selfie was posted to an account called — @robotoverloards, with the bio touting “daily disturbing AI-generated images” as its mission.

@robotoverloards
Asking an Ai to show the last selfie ever taken in the apocalypse Part: 3 #apocalypse #scary #horror #foryoupage #fyp #ai #midjourney #dalle2
♬ It’s Just a Burning Memory – The Caretaker

One image had flashes of light behind the selfie taker, while another showed Earth levitating in the sky, suggesting that humanity has moved to a moon or a different planet. A striking aspect can be seen in the characters, some of which appear looked like aliens or zombies. Another frightening image had a figure in a black plague-type outfit with various other similar haunting figures standing behind them.

This AI-generated futuristic possibility of the end of humankind took social media by storm and resulted in various memes being generated with these wild results.

Although, the creepy predictions and ghoulish grim reapers are not all that Midjourney can do. Some users have tried a more lighthearted perspective and positive images like AI-generated cute pets.

AI Art Software Dall-E Moves Past Novelty Stage, Turns Pro

Disha Chopra

August 5, 2022

Dall-E, a multimodal generative neural model, has moved past its novelty stage. In a recent announcement, Dall-E turned pro and marked a new stage of its life cycle. Although the tool is still in the testing phase, it matures and becomes practical with every other update.

Dell-E was created by OpenAI in January 2021, with the 12-billion GPT-3 parameter version for training the input images. The open and free tool uses standard casual masks for text prompts and sparse attention as rows/columns or convolutional attention patterns.

Almost a year later, in April 2022, the company unveiled Dall-E 2, an upgraded version of its text-to-speech generator with higher resolution and lower latency. This version was only accessible for testing by verified partners constrained in what they may submit or make with it.

In July, OpenAI began giving free access to about 1m users on the waiting list. In the latest updates, the tool will now cost US$15 for 115 credits, where each text prompt is worth 1 credit. Users also receive a few free credits to begin with, and a smaller number of freebies each month.

Dall-E is still in the novelty stage, as evidenced by a recent tweet from ketchup manufacturer Kraft Heinz Co. The tweet included a brief video that demonstrated what happened when Dall-E was given the uncomplicated command “ketchup.” The outcome was a sauce bottle that closely resembled Heinz’s goods.

We wanted to find out what A.I. thinks “ketchup” looks like. So we used A.I. to generate images of ketchup on @OpenAI. The result? Just like humans, A.I. prefers Heinz. Comment below with a ketchup-based image you want to see. #AIKetchup pic.twitter.com/NIPUx0QGWQ
— H.J. Heinz & Co. (@HeinzTweets) July 26, 2022

It may not be artistic to pay AI to sketch a ketchup bottle. Digital illustrators like Krista Webster are concerned that enterprises who contract artists will likely accept the less expensive, computer-generated versions.

IIM Lucknow Opens Applications For Executive Program in AI For Business

Disha Chopra

August 5, 2022

iim lucknow opens applications for ai for business

The Indian Institute of Management (IIM) Lucknow is set to open applications for an Executive Program in AI for Business starting September 4, 2022. The program is specially designed for working professionals who wish to develop their products, services, and processes with AI and data.

The students can apply for the entire online program through the official website. The AI certification program lasts 6 months and is meant for working professionals with 2 to 3 years of experience in machine learning or artificial intelligence.

The curriculum aims to equip learners with the correct knowledge about utilizing efficient technology platforms, tools, and methodologies for AI-driven business applications.

Professor Sowmya Subramaniam, Finance and Accounting, IIM Lucknow, said, “Artificial Intelligence is no longer a fringe technology for organizations. It is important for learners and professionals to upskill as per the changing market conditions and develop a thorough understanding of new technologies.”

The institute collaborated with WileyNXT to offer this online niche program to prospective students, as told by Professor VS, Prakash Attili, IT and Systems, IIM Lucknow. The enterprise will help provide the technical expertise while IIM prepares the students with sharp business acumen.

The candidates who complete the program will be awarded a certificate from IIM Lucknow.

Detect to deploy T-Pulse, an AI-based workplace safety software with Vedanta

Disha Chopra

August 5, 2022

t-pulse workplace safety ai with vedanta

Detect Technologies announced a collaboration with Vedanta, a leading provider of commodities dealing with zinc, silver, lead, and similar metals, to deploy T-Pulse, an AI-powered workplace safety software across the latter’s industries. Vedanta has a wide spread of contractors and employees across India, Africa, Australia, and Ireland.

Managing health, safety, and environment (HSE) for such a vast and spread-out organization can be challenging. Vedanta has been exploring AI-driven solutions to infuse security and efficiency across its network. The development of T-Pulse being piloted across Vedanta has significantly increased the lucency of workplace risks and early detections of more than 4,000 critical HSE non-compliance cases.

Sunil Duggal, CEO of Vedanta Group, said, “This partnership will further augment Vedanta’s capabilities on technology-led safety enablement. Detect Technologies’ AI and computer vision solutions will help us enhance our digital safety monitoring across all business units.”

Per Detec, T-Pulse offers a democratized and scalable solution for plug-and-play deployment. It minimizes and mitigates risks by providing actionable insights for caution-intensive work environments like construction, logistics, mining, petrochemical, pharmaceuticals, and fabrication yards.

Daniel Raj David, CEO and co-founder of Detect Technologies, said, “We appreciate the continued conviction Vedanta has shown in Detect and are excited to enable them in their journey towards improvements in ESG and safety compliance.”

DeepMind’s AlphaFold predicts 3D structure of Every Known protein: Insight into its Milestone

Preetipadma K

August 5, 2022

DeepMind AlphaFold predicts 3D structure of Every Known protein — Image Credit: Juan Gaertner/Science Photo Library

In a recent announcement, DeepMind claimed that it has accurately predicted the three-dimensional structures of almost all cataloged proteins in existence. That includes more than 200 million proteins that can be found in practically anything, including people, animals, bacteria, plants, and plants. Using an AI technique called deep learning, DeepMind’s AlphaFold model can detect the 3D structure of a protein just from its 1D amino acid sequence.

Proteins which are composed of a ribbon of amino acids that folds up into a knot of intricate twists and turns, can be regarded as fundamental blocks of living beings. Because of the intrinsic flexibility of the amino acid building components, a typical protein may take on an estimated 10 to the power of 300 distinct forms. Every protein has its distinct folding configuration, so if one is altered, the protein may misfold and cease to function. Hence, understanding protein folding is highly important.

Consider a locksmith designing a key for a lock. The locksmith needs to be familiar with the structural design of the lock to be able to make the key. Now imagine the locksmith has no access to the information about the lock, they cannot create a key based on the ambiguity of the existence of the lock. Even if they successfully create one, there is no knowing it will work for the said lock. Suppose you think of medicine as a key and protein folds as a lock. In that case, you can see why researchers invest enormous time and effort decoding the folded, 3D structure of a protein they’re working with, much like the locksmith would start their key-making quest by putting together the lock’s mold. Knowing the precise structure makes it much simpler to predict where and how a molecule will bind to a particular protein as well as how that attachment can impact the protein’s folds while developing a cure.

It can take months in a lab to determine that fold—and subsequently, the function of the protein. Scientists have long experimented with automated prediction techniques like X-ray crystallography and cryo-electron microscopy to simplify the procedure. However, no method has ever come close to matching the precision attained by people. Further, they were expensive and time-consuming.

AlphaFold employs deep-learning neural networks trained on hundreds of thousands of experimentally confirmed protein structures and sequences in the PDB and other databases. When presented with a novel sequence, it initially searches databases for similar sequences that can reveal amino acids with a history of coevolving, indicating they are near in 3D space. Another method for estimating the distances between amino-acid pairs in the new sequence is to look at the structures of similar proteins that already exist.

As AlphaFold attempts to represent the 3D positions of amino acids, it iterates clues from these parallel tracks back and forth, continuously updating its estimate. It does this by using the “attention” concept to decide which amino-acid linkages are most relevant for its task at any particular time.

In December 2020, the second iteration of AlphaFold (AlphaFold2) made headlines when it won the Critical Assessment of Protein Structure Prediction (CASP) competition. The competition, which is held every two years, assesses advancement in one of biology’s most difficult problems: figuring out proteins’ three-dimensional (3D) forms only from their amino-acid sequence. In this event, the structures of the same proteins established by experimental techniques such as X-ray crystallography or cryo-electron microscopy, which fire X-rays or electron beams at proteins to build up a picture of their form, are compared to computer-software entries. After predicting structures to atomic accuracy with a median error (RMSD_95) of less than 1 Angstrom – 3 times more accurate than the next best system and comparable to experimental methods – it won CASP14 by a large margin. Further, it was acknowledged as a solution to the 50-year-old “protein-folding problem” by the organizers of CASP.

The scientific landscape had changed significantly since AlphaFold’s formal launch in July last year, when it identified about 350,000 3D proteins. To freely share this scientific information with the entire world, the Google subsidiary published and open-sourced AlphaFold one year ago and also developed the AlphaFold Protein Structure Database (AlphaFold DB). According to DeepMind, the AlphaFold DB acts as a “google search” for protein structures, giving researchers quick access to projected models of the proteins they’re researching. This allows them to concentrate their efforts and speed up experimental work. DeepMind stated that it had mapped 98.5 percent of the proteins used by the human body by the middle of 2021. It also predicted the entire ‘proteomes’ of 20 other widely studied organisms, such as mice and the bacterium Escherichia coli.

Scientists have made remarkable discoveries thanks to the AlphaFold Protein Structure database, which allowed users to see millions of protein structures. For instance, in April, Yale University researchers reviewed AlphaFold’s database to help them achieve their objective of creating a brand-new, potent malaria vaccine. And in July of last year, researchers at the University of Portsmouth employed the method to develop enzymes that will tackle pollution caused by single-use plastics. DeepMind supported World Neglected Tropical Disease Day by developing structural predictions for organisms recognized by the World Health Organization as high-priority for research, therefore advancing the study of illnesses like leprosy and schistosomiasis, which affect more than one billion people worldwide. DeepMind also plans to assist the Drugs For Neglected Diseases Initiative in the following years in identifying treatments for neglected yet widespread tropical diseases, including Chagas disease and Leishmaniasis.

Additionally, DeepMind’s publicly accessible protein structures have been included in other openly accessible databases, including Ensembl, UniProt, and OpenTargets, where millions of people use them on a daily basis.

With the recent release of predicted structures for virtually all cataloged proteins known to science in collaboration with EMBL’s European Bioinformatics Institute (EMBL-EBI), DeepMind has increased the AlphaFold DB’s size by more than 200x, from just under 1 million structures to more than 200 million structures. Researchers envision that this might significantly improve our knowledge of biology. With the inclusion of projected structures for plants, bacteria, animals, and other creatures in this release, researchers now have a wealth of new chances to utilize AlphaFold to further their study on vital topics like sustainability, food insecurity, and unrecognized illnesses.

The recent update will also result in the majority of pages on UniProt’s primary protein database having predicted structures. Additionally, all 200+ million structures will be available for mass download via Google Cloud Public Datasets, offering scientists all across the world even greater access to AlphaFold.

While it seems like Alphafold has achieved its biggest milestone, it is yet to overcome its own limitations to foster new research areas in drug discovery and the pharmaceutical industry. For instance, at present, AlphaFold cannot recognize how proteins alter in form when in contact with chemicals like medicines or other compounds that interact with proteins. Meanwhile, researchers are exploring ways to modify its training dataset and codes that will enable enhanced functionality – apart from its predictions for each amino-acid unit of a protein and associated confidence scores.

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