Baidu has won approval from the country’s authorities to start testing fully driverless taxis on public roads. The Chinese technology and internet services company has received the node to test on 33 individual roads totaling 65 miles in less-populated suburbs. Baidu has already test-driven its vehicles on roads in Beijing, Wuhan, and California. Baidu will soon begin to test it’s driverless taxi on the roads of Beijing.
The announcement makes Baidu the first and only company with permission to conduct driverless tests without a safety driver in the autonomous driving vehicle-on public streets in China’s capital.
Baidu’s driverless taxis will be equipped with the company’s “Apollo” self-driving system, which uses artificial intelligence (AI) to navigate. The company plans to deploy the driverless taxis initially in the Chinese city of Changsha, where it will partner with local taxi firm Didi Chuxing.
In China, Beijing has the most rigorous safety requirements for obtaining approval for driverless testing. According to the conditions announced by the Beijing municipal government last month, autonomous vehicles must complete over 30,000 kilometers of safe test-driving on open roads, have a T3 or higher testing ability, and pass an evaluation on a closed track.
License plates of autonomous driving road tests in Beijing have five levels, from T1 to T5, where T3 indicates that the vehicles possess road condition recognition, emergency disposal, and vehicular traffic laws compliance capabilities.
The driverless testing permits in Beijing are a crucial milestone in Baidu’s plan to build a commercial autonomous driving business. The AI-powered autonomous vehicles could operate in complex urban road conditions. The 5G remote driving service will power all the fully driverless vehicles that will undergo road tests in Beijing. This technology allows drivers to control vehicles remotely in case of an emergency.
Meta’s Research division unveils BlenderBot 3 AI, a competent chatbot built to stand against network toxicity. The company has released a demo version in the US of the 175 billion-parameter conversational algorithm.
Meta believes that AI-driven bots and applications can quickly become corrupt after exposure to the internet’s toxicity if they do not have sufficient and robust behavioral restraints. Chatbots are typically created in highly-curated environments that might limit the source subjects from which the bots take the information. Alternatively, chatbots can be trained by pulling information from the web and accessing a broad range of topics, but this could quickly go south.
Meta researchers said, “Researchers can’t possibly predict or simulate every conversational scenario in research settings alone. The AI field is still far from truly intelligent AI systems that can understand, engage, and chat with us like other humans can.” They also highlighted the need to develop more adaptable and diverse AI models.
Meta has been working to tackle AI-bots’ toxicity in fetching information through the internet since its BlenberBot 1 chat app launched in 2020. Then came the BlenderBot 2 as an open-source NLP (natural language processing) experiment to retain information from previous conversations and search the internet for the source subject.
By assessing both the people and the information it retrieves from them via the web, BlenderBot 3 expands on these skills. Meta researchers recommended people use the demo and share their feedback to help advance the project. They said, “Our live, interactive, public demo enables BlenderBot 3 to learn from organic interactions with all kinds of people.”
The company claims that BlenderBot 3 is anticipated to speak more conversationally than the predecessor, as it is nearly 60 times larger than BlenderBot 2. It provides a 31% improvement in overall rating based on human judgment. Researchers said, “Compared with GPT3, on topical questions, it is found to be more up-to-date 82 percent of the time and more specific 76 percent of the time.”
The Indian Army is enhancing the utilization of surveillance technology to keep watch on China and Pakistan by deploying 140 AI-based surveillance systems along the Line of Control (LOC). These systems will give a live feed of the ground station via high-resolution cameras, UAVs, sensors, and radars.
Artificial Intelligence (AI) will aid the technologies to arrive in the required positions. It will then enable remote target detection and classification, whether a person or a machine. These technologies will be trained to interpret, alter, and detect anomalies and intrusions at the borders. The Army also upgraded its arsenal with other AI-based products for human behavioral analysis, robotic products, etc.
The surveillance units can also monitor social media posts and predict adversary actions in real-time. Additionally, suspicious vehicle recognition systems are deployed in eight locations in Southern and Northern commands to generate counter-terrorism operations intelligence.
The Army has set up the AI Center at the Military College of Telecommunication Engineering, Mhow, Madhya Pradesh, to oversee the surveillance systems. A source at the defense establishment said, “AI is capable of providing considerable asymmetry during military operations and is one of the transformative changes in fighting wars,”
The Army is also seeking 5G technology to aid battlefield operations. The high-bandwidth connectivity will give an upper hand to frontline troop communication. The Army is conducting joint studies with the Corps of Signals to implement 5G appropriately. It has also signed an MoU with IIT-Madras to expand the investigation.
Incorporating AI into national security surveillance will also considerably reduce the requirement for manual monitoring.
According to an IDC report, banks across the world will spend about an additional US $31 billion by 2025 on artificial intelligence (AI) installed in existing systems to reduce fraud.
The report also mentions fraud management as a foremost priority for banking executives.
According to Michael Araneta, Associate Vice President, IDC Financial Insights, businesses might be overestimating the adequacy of their current defense mechanisms against fraud in coming up with digital products and services.
Araneta added that what worked well before would not be enough now in the more digitized business world. There must be a constant upgrade of fraud management strategies.
According to the report, the banking industry is facing two crisis scenarios, each side requiring solutions that can run counter to each other. Both government policy and financial services institutions must balance between the chase for revenue and risk management.
The industry will also be involved in platform-building by 2023, which allows financial services to be extended and externalized to third parties, said the report.
Araneta said that the industry is pursuing new collaborations like banking as a service (BaaS) and digital lifestyle ecosystems. He added that being digital-first means being attuned to the critical moment in the recovery of financial services.
With the recent advancements in computing power, quantum computing is gearing up to revolutionize the needs of today’s modern world. Quantum computers can easily solve complex problems that are difficult and, in most cases, impossible for traditional computers to process. Moreover, quantum machines can solve complex problems a billion times faster than classical supercomputers. Such speed and accuracy unlock countless possibilities in almost every aspect of modern life.
Several technological giants are strategically investing in quantum computing. Recently, IBM updated its quantum computing roadmap, which suggests that IBM will accelerate quantum’s expected trajectory by developing quantum processors that have the potential to scale to hundreds of thousands of qubits several years earlier than expected. If IBM’s roadmap is implemented successfully, it will change the quantum computing paradigm.
Considering the hype around the topic of quantum computers, one often wonders what their real-world applications are. To answer that, this article discusses the top applications of quantum computing.
One of the top applications of quantum computing is its utility in research in the field of particle physics or high energy physics. Particle physics models are highly complex. Hence, require lengthy computing time and a vast number of resources for numerical simulations. For instance, consider the example of the Large Hadron Collider (LHC) at CERN. Experiments on LHC produce one petabyte per second of data resulting from collisions of one billion particles every second, which is impossible to keep up with. Here’s when quantum computing comes to the rescue.
Quantum computers enable physicists to deal with vast experimental data with accuracy and speed. They also allow one to simulate nuclear experiments and fundamental interactions, including scattering the nuclei and quarks. The computing power required to process LHC data is expected to increase by a factor of a hundred by 2027. In 2019, CERN initiated its collaboration with IBM to work on quantum computers.
2. Training Artificial Intelligence
Quantum computing applications include the crucial task of training artificial intelligence. The intelligence demonstrated by machines requires training; quantum computing can simplify the task of analyzing millions or even billions of data points with accuracy and speed. In 2020, Google, in collaboration with Volkswagen and the University of Waterloo, launched TensorFlow Quantum to accelerate development in quantum computing. TensorFlow Quantum is an open-source library used for prototyping quantum machine learning models.
For specific artificial intelligence models, quantum machine learning is much more suitable than classic machine learning. Quantum machine learning explores methodological and structural similarities between specific learning and physical systems, specifically neural networks.
3. Financial Modeling
One of the top applications of quantum computing includes its use in financial modeling. Based on expected returns and associated risks, finding the right mix for profitable investments is significant for financial investors to survive in the market. This process involves the analysis of thousands of factors that have the potential to affect stock prices. On classical computers, Monte Carlo simulations are used by investment banks for detailed analysis. However, this method takes a vast amount of time and computing resources.
Since quantum computers are mainly designed for such probabilistic calculations, by using them, investment banks can enhance the quality of their solutions and significantly decrease the time required to develop them. In the long run, quantum computers can assist financial services in opening new investment opportunities by increasing investment gains and reducing capital requirements.
4. Drug Development
The development of drugs is on the list of top applications of quantum computing. It can take over ten years and billions of dollars for pharmaceutical companies to discover or develop a new drug, for which scientists run hundreds of millions of comparisons on conventional computers. However, the processing capabilities of traditional computers are limited as they can analyze molecules only up to a specific size. This issue can be rectified with the use of quantum computing.
As quantum computing algorithms and hardware become more prevalent, they will make the comparison of much larger molecules possible. This can drastically reduce the time and costs involved in drug development, thus empowering scientists to find cures for various diseases faster than expected.
5. Advertising and Marketing
Applications of quantum computing in advertising and marketing are revolutionary. Quantum algorithms can help create and deliver better advertisements by interpreting associations influencing purchasing patterns. Instead of just using browser history for ad delivery, quantum algorithms focus on factors like how users feel after looking at an advertisement and what types of ads could help make long-term relations with the customers.
In collaboration with Recruit Communication, D-Wave Systems has pioneered the application of quantum computing to optimize marketing, advertising, and communication. They aim to use quantum computing in advertising to analyze complex data in less time and increase the efficiency of delivering advertisements to their targeted customers.
6. Discovery of New Materials
Applications of quantum computing include the discovery of new materials. Quantum computing is based on quantum-mechanical phenomena; hence, it can represent other quantum systems more efficiently than conventional computers. For instance, consider Schrödinger’s equation. A quantum machine can solve Schrödinger’s equation for a molecule to accurately calculate its allowed energy states. Quantum computers can also simulate complex molecules that conventional computers are unable to.
Researchers can develop optimum materials with finely tuned mechanical and optical properties by handling the noise in the qubits on quantum machines. Recent advances in quantum noise-canceling techniques suggest that next-generation materials might be designed on quantum computers rather than by traditional trial and error. Further advancements in quantum algorithms and hardware can revolutionize theoretical chemistry.
7. Development of Nitrogen Fertilizers
The development of clean fertilizers is one of the quantum computing applications. Quantum computers are gearing up to model the primary cofactor of nitrogenase, i.e., the FeMo cofactor. This advancement can enable chemists to develop energy-efficient industrial processes for synthesizing nitrogen or clean fertilizers.
Currently, ammonia fertilizers are developed through a Haber-Bosch process that uses enormous amounts of energy and releases large amounts of greenhouse gases. However, quantum computers can find the nitrogenase mechanisms and behavior of transition metals in detail, allowing the development of more efficient catalysts for manufacturing fertilizers.
8. Traffic Control
Quantum computers can also help tackle the problem of traffic control, which is a result of the increasing population. Technology using quantum computing can be used to mitigate traffic jams and thus shorten waiting periods. Recently, Volkswagen demonstrated the use of quantum computing to optimize traffic in a live setting. The D-Wave quantum computer used by Volkswagen’s quantum routing algorithm calculates the fastest travel routes in real-time.
Quantum routing algorithms can augment the entire mobility system of a city and can constantly interact with moving objects on the road. These algorithms can also be utilized in air-traffic control for enhanced routing information. Several other automobile manufacturers, including Toyota, BMW, and Ford, are investing in quantum computing applications.
9. Cybersecurity
Enhancement of cybersecurity is one of the most crucial applications of quantum computing. Quantum computers can crack encryption algorithms that protect the infrastructure and sensitive data of the internet. Estimates predict that a quantum computer with 20 million qubits is capable of breaking such encryptions in less than 8 hours.
Moreover, quantum computing can also be used to build much more secure encryption systems. Companies like Google and Microsoft have initiated their work on quantum-safe encryption algorithms. Although they are currently in the testing phase, quantum-safe algorithms are expected to assist with securing banking transactions, military communication, medical records, etc.
10. Efficient Weather Forecasting
One of many applications of quantum computing is mapping complicated weather patterns. Unlike traditional weather forecast systems, quantum computers can provide forecasts for much smaller and more specific areas. This can assist farmers in preparing for weather changes efficiently and allow airlines to minimize fight disruption.
In collaboration with the National Center for Atmospheric Research, The Weather Company, and the University Corporation For Atmospheric Research in the United States, IBM is building a quantum computing model that can estimate thunderstorms at a regional level. Quantum computing systems can also forecast micro-meteorological events, such as the formation of individual clouds or wind eddy by processing extensive meteorological data.
11. Enhanced Batteries
Researchers at IBM and Daimler AG are testing how quantum computers can simulate the behavior of chemical compounds in Lithium-ion batteries. They were able to simulate dipole moments of four industrially relevant molecules, viz. lithium sulfide, hydrogen sulfide, lithium hydride, and lithium hydrogen sulfide, using a 21-qubit quantum computer. As scientists increase the qubit states, they will be able to test more complex compounds to develop next-generation batteries that would be more powerful and inexpensive.
Conclusion
Overall, quantum computing is taking giant leaps in shaping several domains of everyday life, ranging from traffic optimization to cybersecurity. According to GlobeNewswire, the global market for quantum computing was valued at US $507.1 Mn in 2019, and it is expected to reach US $4531.04 Bn by 2030.
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.
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 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 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.”
The gaming industry was valued at USD 198.40 billionin 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.
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.
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.
