The Department of the Air Force recently awarded SandboxAQ, an enterprise SaaS company that provides governments and the Global 1000 with the cumulative benefits of AI and quantum (AQ) technology, a Phase 1 Small Business Innovation Research (SBIR) contract to carry out post-quantum cryptographic inventory analysis and performance benchmarking.
As part of the agreement, SandboxAQ will evaluate the encryption currently in use and identify any software enhancements that offer an end-to-end, crypto-agile framework to protect the Air Force and Space Force data networks from potential quantum technology-based attacks. It is known that Phase 1 SBIR payments typically range from $225,000 to $350,000 for projects lasting 6 to 12 months. Nevertheless, the company chose not to reveal the contract’s financial details.
This new partnership, which is a part of the Air Force’s effort to get ready for The Quantum Computing Cybersecurity Preparedness Act, which mandates that US federal agencies upgrade to post-quantum encryption, is SandboxAQ’s first military contract since being spun off from Alphabet in March earlier this year. In general, the collaboration between the Air Force and SandboxAQ shows that the risk posed by post-quantum computing is real, for which businesses must start preparing.
The SandboxAQ software package simplifies the implementation of post-quantum cryptography. The startup claims that its software package includes both conventional and encryption techniques resistant to quantum technology. There are also a number of tools included that can make it simpler for businesses to integrate the algorithms into their applications.
The corner stone of The New York Federal Reserve Bank REUTERS/Brendan McDermid
Following the FTX meltdown, the US agreed to begin experimenting with a CBDC (central bank digital currencies) digital dollar over the following 12 weeks. On November 15, the Regulated Liability Network (RLN), a proof-of-concept digital currency platform, was made public by the Federal Reserve Bank of New York’s Innovation Center (New York Fed), or NYIC.
According to the New York Fed, the initiative would investigate the viability of a shared multi-entity distributed ledger on a regulated liability network that operated as an interoperable network of central bank wholesale digital money and commercial bank digital money. It will engage central banks, commercial banks, and regulated non-banks to enhance financial settlements.
As part of the pilot, massive financial institutions, including BNY Mellon, Citi, HSBC, Mastercard, PNC Bank, TD Bank, Truist, U.S. Bank, and Wells Fargo, will issue tokens and settle transactions using simulated central bank reserves to represent US Dollar via a shared multi-entity distributed ledger. The technology for the pilot initiative, which will be used in a test environment, is being provided by SETL and Digital Asset.
According to the group, the initiative would have a regulatory framework that is in line with current laws requiring know-your-customer (KYC) and anti-money laundering measures. The viability of expanding the platform to include additional digital assets like stablecoins will also be investigated.
Following the completion of the study, the group says it will disclose the results of the pilot program, but participants are not compelled to engage in future endeavors.
Michelle Neal, head of the New York Fed’s market department, stated earlier this month that the central bank saw promise in adopting a digital dollar to shorten settlement times in currency markets. Banking authorities have long been interested in CBDCs, which similar to stablecoins, are digital representations of a state’s fiat currency that are paired 1:1 with a particular fiat currency. But, while stablecoins produced by central banks might aid in the fight against fraud, they ultimately maintain the centralized structure of FIAT currency and plainly include a mass monitoring component.
It is unclear what kind of regulatory structure the US would adopt for cryptocurrencies, especially given that the collapse of FTX appears to have set the tone for a complete prohibition. Even though the EU and UK are also investigating CBDCs, at least their legislative initiatives seem to be in favor of crypto assets. Meanwhile, China has made progress in this direction by testing the digital yuan since April in numerous regions, and the currency is even available to WeChat users. Recently, it has added four provinces to its list of CBDC testing regions. In September, Australia announced a pilot project for a digital dollar based on Quorum, an enterprise-grade, private variant of Ethereum. Last month, the Reserve Bank of India (RBI) announced a pilot of its version of CBDC.
The NYIC pilot initiative was introduced shortly after the center released research on its wholesale central bank digital currency initiative on November 4. Project Cedar, the first stage of the CBDC experiment, investigated foreign exchange spot trades to see if a blockchain solution might speed up, lower the cost of, and provide easier access to cross-border wholesale payments.
In a related development, on November 10, the New York Fed and the Monetary Authority of Singapore (MAS) launched a collaborative experiment to see how wholesale CBDCs could simplify multi-currency cross-border payments.
Advait Danke, an Indian DJ, spiritual catalyst, and sound alchemist, has officially launched the ‘Resonance Living Mindful Metaverse,’ called the first sound meditation metaverse to be launched in India.
The newly-launched metaverse is easy to navigate and user-friendly. It can be accessed through mobiles, laptops, and desktops on the Spatial App. To provide a hassle-free user experience, the metaverse developers have ensured that there is no login issue and no subscription fee is charged, thus providing free access to everyone.
The platform has immersive visuals and mindful movements that give the user a spiritual and meditative experience. Further, this experience can be enhanced by incorporating VR headsets. The metaverse was co-developed with the team at Wow Labz, Xarvel, and Metawood.
Since its launch, the platform by Advait Danke has been appreciated by people for its unique, engaging features and for bringing forth the concept of how the science of sound, music, meditation, and consciousness combined impacts human body-mind energies.
Advait also integrated blockchain technology into the metaverse through “The Sounds of Universe,” an enduring audio NFT collection based on the science of brainwave technology. The audio NFTs induce mindful musical patterns and vibrations to impact an individual’s mental and emotional state positively.
Abu Dhabi will launch a Metaverse version of its entertainment capital, Yas Island, as its entertainment arena has various sections like theme parks, homes, aquariums, and malls. Moreover, the island is accessible to a global audience.
Yas Island is the entertainment capital of the UAE. The country has a total of 200 islands, but in 2023, one more island will be added. This will be unique because it will be a digital island.
Once it is set up, the audiences can meet up or play games while exploring the digital island. The CEO of Miral, Mohammed Abdalla Al Zaabi, announced the initiative.
According to him, VR is the best medium for a global audience to discover Yas Island uniquely. He added that the visitors would be able to create virtual homes and even theme parks.
The central tourist attraction will be the Ferrari World, where visitors will get a chance to ride the world’s fastest rollercoaster F1 racetrack.
India will be taking over the chair of Global Partnership on Artificial Intelligence (GPAI) from France today, November 21. Rajeev Chandrasekhar, Minister of State for Electronics and Information Technology, will represent India at the GPAI meeting in Tokyo as the symbolic takeover from France.
The development comes in light of India assuming the Presidency of the G20, which is a league of the world’s largest economies. GPAI is an international initiative to support human-centric development and the use of artificial intelligence.
The GPAI comprises 25 member countries, including the US, UK, Italy, Japan, Mexico, New Zealand, South Korea, Singapore, European Union, Australia, Canada, France, and Germany.
India joined the GPAI in the year 2020 as one of its founding members. Artificial intelligence is expected to contribute $957 billion to the Indian economy by 2035. It may also add $450 to 500 billion to the GDP of India by 2025, accounting for 10% of its 5 trillion dollar GDP target.
India occupying the chair also signifies how today’s world perceives it as a trusted technology partner and has always advocated for the ethical use of technology to transform citizens’ lives.
Nowadays, many business owners have a site for their products or service. However, poor website design would lead bad impression for the website viewers, and it causes businesses to lose customers and money. That’s why we are going to explain these 13 mistakes in the design of your website.
Avoid these 13 mistakes when designing your website
1. You’d rather avoid justified text
Justifying the texts is one of the mistakes made on many web pages, thinking that it is usually done quite a bit in print. However, in the digital world, it is not so appropriate. Why? Justified texts cause readability problems for the user. Although an editor can correct this in paper format manually, on the web, this is not the case. Better avoid it!
2. Use of capital letters that bother
The texts in capital letters attract more attention, it is true, and that is why they are sometimes used to highlight some headers on the web. But beware! If there are too many words in capital letters, in the end, you are not highlighting anything, and then you can do your website a disservice by creating an effect that makes it difficult to read.
Also, READING IN CAPITAL LETTERS IS UNCOMFORTABLE. The truth is that it gives a little sensation that they are yelling at you. So, keep this in mind: don’t capitalize long paragraphs that span multiple lines or no one will want to read them.
3. Impossible-to-read fonts
Although it is not one of the most common errors, we still see websites that use fonts that are far from comfortable for the user. For example,” script” or “hand draw” typefaces are not very reader-friendly. They can be used in your website logo, headers or subheaders, but it is not recommended for web text.
And it is not only the typography that makes a text readable. The size is also important. According to Google, the recommended minimum size for text is 16px. This will also depend on the font type, but the ideal knows how to find a balance if you want users to be safe.
4. Creepy Color Scheme
This type of failure, on the contrary, is one of the most common. If you need a designer to create your website, it is more common for this to happen since there is no professional behind it to ensure that the color scheme is consistent and provides a good user experience. Although without a designer, it is already something that could be detected, so you can judge for yourself if those colors hinder your browsing experience or if they give you a bad feeling.
Even so, disasters are normal if you do not have a web design professional. And, if you want to get away from the typical white background and black text, try to make the contrast strong enough so that the readability of the text is not affected. Do not put a red background unless you want to scare the user.
5. Complex navigation that loses you along the way
That the navigation of your web page is simple and intuitive is a crucial factor for the user experience. The user must manage to get to what he is looking for with the least number of clicks possible.
You probably won’t have this problem if your web page is small. However, it is more common for navigation to become more complex on websites with many services and products or a blog with many categories.
For example, if you have different pages: about us, our values, our mission. They could all be combined on the “About Us” page. Thus, you would reduce the number of items in the menu, gather pages that share a common theme (about us), and still have an adequate number of levels.
On some occasions, this will do your website a great favor by providing a logical content structure, and obviously, you will also do the user a great favor. In others, it will be necessary to make a separation, and you will not be able to resort to this. But, of course, if each of these pages only has a couple of paragraphs, it is better to combine them into one.
6. The overwhelming use of white space
Trying to highlight all the services, products and offers in the same space to try to ensure that the user who enters does not miss anything is far from achieving what you want. What this does rather is saturating the user with too much information. It is much better to whitespace your website content to make it easier for the user to focus on a clear call to action. In addition, it will give a respite session by finding blank spaces that make you rest from the content.
7. Endless blocks of text
As we said before, writing on a website doesn’t have much to do with a Word document. Neither kilometric paragraphs nor justified text. You just have to think that if a text can be long on a desktop or on mobile, it could be twice as long. And yes, currently, more websites are viewed from mobile devices than on desktops.
8. Pages that do not contribute anything
I have come across many web pages with sections in which the content is two paragraphs or just an image that does not add anything of value. You have to review your website and see if there are sections that you can perhaps combine or eliminate in case they do not add value to the user. In this way, you improve web browsing, reduce the number of pages that Google has to track, and generally improve the user experience.
9. Creepy use of H tags
Not using the <h1> tag, placing several <h1>s on a single page, not using a well-structured <h2> or <h3> to the <h2>s, using headings for the style they have, without taking into account the SEO on Page, etc. Misusing H tags will harm the positioning of your website and will make the user feel lost because there will be no coherence in the text they are reading.
10. Lurid colors that make you want to scream
Avoid using colors that are too strong or too light so as not to make reading difficult for the user. For plain text and headers, it is best to use black or dark gray shades. It’s okay if you want to highlight a word in color but try to make it just that.
11. Not responsive content for other devices
It is essential to make sure that all the pages of your website look good on mobile. As we said before, viewing websites from a mobile format is now more common than doing it on a desktop. It is much faster to make a query from your mobile, which you probably have very close, than from a computer. Therefore, it is critical to design for mobile, even more than for desktop.
12. Images that weigh too much
Without a doubt, one of the most common mistakes is remembering to optimize images. Its resolution and weight play a very important role on your website since heavy images are one of the things that most affect the loading speed and one of the most critical factors in the user experience. Nobody waits much more than 3 seconds. If a website does not load all the content, it is easier to go out and find another website that does. What experience are you providing?
13. Contact details that live hidden
Does this happen normally? Well, yes, even if you think it’s something strange to see, because who wouldn’t want to have the contact visible? The contact information on your website must be easy to locate, especially if you offer urgent services. Therefore, the idea is that the user always has a way to contact you, either by phone or email, just one click away.
Conclusion
Now you can put all these info into practice with your website, right? Try not to make any of these catastrophic mistakes. Otherwise, you will suffer the consequences of the positioning of your website!
A new Python library, built on PyTorch, called ‘TorchOpt,’ enables developers to run differentiable optimization algorithms like OptNet, MGRL, MAML, etc. DIfferentiable optimization is an emerging practice to enhance the sampling efficiency in machine learning models. However, none of the existing optimization libraries can fully enable the execution of these algorithms, or they focus only on a small subset of differentiable optimizers.
To become efficient in differentiable optimization, models must differentiate through the inner-loop optimization process to generate the gradient term of outer-loop variables (or meta-gradient). Meta-gradients can significantly improve the sampling efficiency of machine-learning models. But, there are several difficulties in developing optimization algorithms.
Firstly, developers must successfully realize different inner-loop optimization techniques before implementing differentiable optimization. Secondly, it requires a lot of computation due to large batch sizes, high-dimensional linear equations, Hessian calculations, etc. TorchOpt solves many of these problems by running optimization algorithms with multiple GPUs.
It offers a “unified and expressive differentiation mode” to run optimization algorithms on computational networks created using PyTorch.
It offers three differentiation techniques: explicit gradient for unrolled optimization, implicit gradient for differentiable optimization, and zero-order gradient estimation for differentiable functions.
It comprises CPU/GPU accelerated optimizers for distributed runtime and high-performance execution.
Parallel OpTree for nested structure flattening or Tree operations.
TorchOpt effectively cuts the training time and enhances machine learning models. It is open source and is readily accessible via GitHub and PyPi.
After the big data revolution, majority companies are shifting to data-centric operations. These operations require specially trained professionals for ‘data sciences.’ Data science is an emerging domain that combines the knowledge of mathematics, statistics, and computer science to work on data-centric problems in the real world. People, called ‘data scientists,’ study and ultimately utilize the knowledge to help organizations make sense of their data. Data scientists analyze the collected data, make it usable and generate insights from it, using which organizations make decisions. To become a proficient data scientist, one needs to do a comprehensive postgraduate course and become familiar with the all gritty details and concepts.
Data Science Postgraduation Courses
Here are a few good Data Science postgraduation courses.
Symbiosis Centre for Information technology (SCIT) – MBA in Data Sciences and Data Analytics
SCIT offers postgraduation data science via its MBA course. The MBA in Data Sciences and Data Analytics course aims to guide management professionals in a career in data-related technologies. With this data science PGDM, students will learn to use hands-on tools and gain analytical competencies. On completion, the students will be prepared for techno-functional and business-oriented roles in data projects and companies.
It is a full-time two-year residential program open to graduates from recognized universities with a minimum of 50% marks or equivalent grades. Lastly, the applicants must have had Mathematics as a compulsory subject in 10+2.
NIIT – Advanced PG Program in Data Science and Machine Learning
NIIT offers an Advanced PG Programme in Data Science and Machine Learning to help students gain expertise in data analysis visualization, modeling, natural language processing (NLP), and other related technologies. Through this course, students will work with RDBMS (relational database management systems) and deep learning frameworks and do predictive modeling for several industry-specific use cases.
It is a full-time online course over 18 weeks and is open for graduates with more than 50% marks or equivalent in 10th and 12th standards and graduation. The data science postgraduation course also provides placement assistance for students who pass the eligibility and are less than 25 years of age.
IIT Madras – PG Diploma in Data Science
The Indian Institute of Technology in Madras (IITM) offers a comprehensive PG Diploma in Data Science. The course is open to college students, working professionals, and job seekers who wish to advance their careers in the data science domain. Through the course, students will become familiar with programming in Java, and Python, designing databases, developing APIs, advanced SQL, and full-stack development.
It is an online data science PG diploma programme that will take about 8 months to complete. It will include 8 courses and 2 hands-on projects involving business analytics and statistical modeling. Students who have completed their 10+2 and wish to join the course must give a qualifier examination to enroll in the course.
IISc Bangalore – MTech Computational and Data Sciences
The department of Computational and Data Sciences (CDS) at IISc Bangalore offers two degree programs involving research, a Ph.D. and an MTech. The MTech Computational and Data Sciences postgraduate program primarily focuses on interdisciplinary coursework. Through this course, students will learn about domain-specific sciences and areas of computing. Students will take 36 credits of coursework over 2-3 semesters. Lastly, the students must complete a dissertation project within 12 months to be certified in foundational and computational systems.
To enroll in this two-year MTech, students must provide their GATE scores to get shortlisted for the online qualifier examination and interview. The GATE score will carry 70% weightage, and the remaining 30% comprises the online test and interview.
IIIT Lucknow offers a Post Graduate Diploma in Data Science to help working professionals become experts in data warehousing, big data analytics, Python programming, intelligent agent & planning, and machine learning. Through the course, students will have 2 hours of online instruction daily and will have 2 weeks to complete each subject. There will be 10 subjects and 2 hands-on projects, after which the students will be graded.
On completion, the students will be familiar with all necessary data technologies to advance their careers in this emerging field.
UPES – Distance Postgraduation Data Science
UPES is an accredited university offering a distance PG Programme in Data Science to graduated students with prior programming experience. It is a comprehensive course that covers commonly used programming languages, mathematical concepts, statistical modeling, and business aspects. Students will also get exposure to SQL, R, Python, and Tableau.
It is a 10-month online data science course for professionals who wish to advance their careers in business data analytics. It will also cover domain-specific topics, banking, e-commerce, power, aviation, logistics, and supply chain management. Any graduate with a minimum of 50% marks in graduation can enroll in this course.
IIT Hyderabad – MTech in Data Science
IIT Hyderabad offers a data science postgraduate program that is an extension of its Executive MTech in Data Science (EMDS) programme. Resided by the CSE department, the new MTech in Data Science (MDS) programme is a self-paced course that helps students learn about data technologies and their applications. Additionally, students will have the opportunity to be a part of two Capstone projects.
The programme is specifically designed for working professionals with a BTech/BE degree in CS/EE/IT/ECE or an MCA/MSc/MS/ME in CS/IT. The students must have at least 70% or an equivalent grade in the degrees mentioned above. The selection process will involve a written test conducted at IIT-H followed by online interviews.
VIT – M.Sc. in Data Science
The School of Advanced Sciences (SAS) at the Vellore Institute of Technology (VIT) offers a comprehensive postgraduate M.Sc. degree in data science. The degree will help graduates become proficient in statistical data analysis and modeling by imparting theoretical as well as practical knowledge. The students who enroll in the course will also work on database manipulation, preparing them for emerging roles in data science and analysis. The course will cover linear algebra, regression analysis, predictive analytics, time-series analysis, and multivariate data analysis.
It is a two-year course open to students with formal and regular graduation with more than 50% marks or equivalent grades. On completion, the students will receive placement assistance for roles in IT firms, market research companies, e-commerce, pharmaceutical & healthcare, banking, and other financial services.
Christ University Bangalore – M.Sc. in Data Science
The reputed Christ University offers a postgraduation data science course focusing on technical aspects and hands-on practical exposure. It offers an interdisciplinary curriculum, including electronics, mathematics, statistics, and probability. Through the course, students will become familiar with data mining techniques, programming, data analytics, and storage. The course will also impart practical skills like project management, reasoning, teamwork, and decision-making via workshops, seminars, group discussions, etc.
It is a full-time, two-year-long postgraduate program open to students with a minimum of 50% marks in BCA/Bachelor in CS/Mathematics/Statistics.
Fergusson College – M.Sc. in Data Science
The M.Sc. postgraduation data science offered at Fergusson College will provide an excellent opportunity for students to learn domain-specific hands-on skills. Students will develop a practical attitude and interest in data-driven research through the course. They will learn about data formats, languages, processing, and management. Throughout the duration, the focus will be on students’ holistic development by making them work hard and as team players.
It is a full-time, two-year-long postgraduate course open to students who graduated from accredited institutions.
Generative models capable of automatically producing text paragraphs or digital art are becoming increasingly accessible. People use them to write fantasy novels, marketing copy and create memes and magazine covers. For better or worse, content automatically created by the software is bound to flood the internet as artificial intelligence technology is commercialized. And with that, the controversial question being asked is, can AI art be copyrighted? For example, current US laws only grant copyright protection for works created by humans. However, the creative nature of neural networks is causing some to consider whether it might be worth changing them.
Consider Cosmopolitan’s recent magazine cover, which they claimed is the “world’s first artificially intelligent magazine cover.” It’s the image of an astronaut walking on a planet against a dark sky with stars and gas, produced by OpenAI’s DALL-E 2 model. A creative director, Karen Cheng, described trying several texts prompts to guide DALL-E 2 to create the desired picture. She then edited the image to create the final cover for the glossy magazine. Who owns the copyright? Who is the author of the image?
PSA: The world’s smartest artificial intelligence (aka @OpenAI) made this magazine cover (yes, really!)—its first EVER. pic.twitter.com/vgLOuKSQ4s
According to a copyright lawyer from Rosen, Wolfe, and Hwang, Mike Wolfe, the answer depends on how much human input went to create something. “Where AI has played an essential role in creating a work, there are still pathways to some copyright protection. Even with a very capable AI, there will probably be a lot of room for human creativity. If AI helps generate a song and makes the bass line, but the creative professional makes it more complete by filling in gaps to make a cohesive piece of music, that act itself would likely give the right to copyright based on human authorship,” he said.
What that could mean in practice is perhaps the melody or bass line could be used freely by a third party as those parts were generated by a machine and are not protected by copyright, but people cannot copy the whole song verbatim, Wolfe said. In reality, however, separating human and machine labor may not be easy. Going back to the instance of the Cosmopolitan front cover, it is not clear entirely which parts of the image are created by DALL-E 2 and which parts are by Cheng.
Founder of a software company based in Missouri, Stephen Thaler, learned this the hard way. The US Copyright Office rejected his application to register authorship to AI for a digital image that he claimed was autonomously made by a computer algorithm running on a machine. He wanted his software to get the authorship of the picture and for the copyright of the image to be transferred to him, as he owned the machine.
The US Constitution granted Congress the right to protect IP in Section 8 of Article I: To promote the progress of science and useful arts by securing for limited times to inventors and authors the exclusive right to their respective writings and discoveries. Countering that, Thaler said, “AI can make functionally creative output in a traditional human author’s absence, and protecting AI-generated works with copyright is crucial to promote the production of socially valuable content. Providing this protection is required under current legal frameworks.”
But not all legal experts agree with Thaler. “The burden should always lay on the creator to prove that the copyright they get benefits the public. I think that burden has not been carried by machines. Granting rights to AI-generated works does not at this time seem likely to make us more advanced or wealthier,” Wolfe said.
Conclusion
So, can AI art be copyrighted? Do we really want to treat machines as equals in the eyes of the law? As of now, there doesn’t seem to be much a lot of appetite for that. But the calculus might inevitably change as you see more impressive outputs from these potent systems. A New York City-based artist, Kris Kashtanova, a former programmer, recently announced that Zarya of the Dawn, an AI-generated graphic book, has been registered for US copyright. It could be the first content produced utilizing AI-art generators to get such recognition from the US Copyright Office, considering other authors’ previous inability to achieve this milestone. Perhaps this is the start of the unprecedented.
Accenture is expanding its AI division with the acquisition of Albert, a Japanese data science startup, following the completion of a tender bid. The deal, which was finalized on November 14, would allow Accenture to expand its data and AI capabilities by bringing 250 data scientists from Albert on board.
Accenture claims that the amount of common shares and stock acquisition rights tendered to Accenture by ALBERT considerably exceeds the amount necessary for ALBERT to merge with Accenture, which is equal to two-thirds of ALBERT stock. ALBERT will become a part of Accenture when the deal is completed. Following the acquisition of all outstanding shares and stock acquisition rights by Accenture, ALBERT will be delisted from the Tokyo Stock Exchange.
ALBERT primarily serves large Japanese organizations with its AI and big data analytics services, AI-based algorithm creation, AI implementation consulting, and data science training assistance. The company was founded in 2005, and in 2015 it was listed on the Tokyo Stock Exchange. Its 250-person data science team will join Accenture’s Applied Intelligence practice, which provides AI and data-driven transformation solutions and services.
Accenture believes that ALBERT will improve its ability to help its clients manage the complete reinvention of their businesses, which most successful organizations will go through in the upcoming decade.
Albert is the most recent in a line of data, and AI-related Accenture acquisitions since 2019, including Analytics8 in Australia, Sentelis in France, Bridgei2i and Byte Prophecy in India, Pragsis Bidoop in Spain, Mudano in the UK, and Clarity Insights, End-to-End Analytics, and Core Compete in the United States.
Accenture’s acquisition is the latest endeavor in the company’s efforts to improve its services in Japan, which leverage data to replicate the entire enterprise digitally and to help Japanese companies grow and become more competitive through deep data analytics and AI capabilities. Accenture recently introduced a number of data-driven management solutions in Japan, including those that anticipate different business scenarios, suggest measures to enhance the forecasts, and support customers’ ESG (environment, society, and corporate governance) practices.
Companies nowadays require a 360-degree view of their business in order to make better and faster decisions, according to Atsushi Egawa, who oversees Accenture’s business in Japan. This means considering factors other than the numbers, such as environmental efforts, customer experiences, the growth of employees, and retraining.
Atsushi said, “Gaining this holistic perspective and being able to simulate every aspect of the business requires deep data science expertise and AI capabilities. Accenture and Albert team will bring these to clients to help them succeed in their total enterprise reinvention.”
