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The advent of the Fourth Industrial Revolution and its accompanying technological advancements has commanded the attention of countries worldwide, leading to an unprecedented adoption and interest in leveraging artificial intelligence (AI). As AI increases in ubiquity, countries in the Global South, including Africa, Southeast Asia, Latin America, and the Caribbean, have begun to capitalize on the opportunities presented by these technologies despite early development being primarily concentrated in the West. Given the historical development challenges that countries in the Global South have faced, AI stands to help advance progress in critical domains such as agriculture, healthcare, and education. However, rising concerns about the ethical implications of using AI also present new challenges for countries in this region to address, along with handling existing development priorities.

As the development of AI advances rapidly and demonstrates the potential to bolster economic growth, governments in the Global South must understand how to make progress toward enacting robust AI regulation and building thriving AI ecosystems that sustainably support startup growth and the development of research and engineering talent. A part of this progress will involve the equitable inclusion of countries from the Global South in roundtable convenings, working groups on AI, and high-level advisory bodies such as those initiated by the U.K. government, OECD, and the United Nations. However, the inclusion of the Global South in these initiatives should also be a goal of countries that have dominated the current AI discourse. The White Houses plans to lead critical global conversations and collaborations on AI, as outlined in the recently issued Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, should deliberately seek participation from stakeholders and governments in the Global South to inclusively work towards an equitable era of AI.

Current landscape of AI in the Global South

Over the past decade, the Global South has adopted AI tools to address traditional development challenges, and there exists a diverse array of use cases for AI among member countries in the Global South, particularly in agriculture, healthcare, and education. Within agriculture, projects have focused on identifying banana diseases to support farmers in developing countries, building a deep learning object detection model to aid in-field diagnosis of cassava disease in East Africa, and developing imagery observing systems to support precision agriculture and forest monitoring in Brazil. In healthcare, projects have focused on building predictive models to keep expecting mothers in rural India engaged in telehealth outreach programs, developing clinical decision support tools to combat antimicrobial resistance in Ghana, and using AI models to interpret fetal ultrasounds in Zambia. In education, projects have focused on identifying at-risk students in Colombia, enhancing English learning for Thai students, and developing teaching assistants to aid science education in West Africa. There is much anticipation for an increase in AI innovation over the next decade as companies, governments, and various organizations actively work to expand their development.

The emergence of AI within the Global South has also provided opportunities to democratize current AI practices, lead towards the development of more inclusive AI systems, and increase participation from communities underrepresented in AI development. Grassroots organizations, such as Masakhane and Ghana NLP, have emerged to focus on developing datasets and machine translation tools to help expand access to low-resource African languages. Efforts such as Deep Learning Indaba, Khipu, AI Saturdays Lagos, and Data Science Africa, amongst many others, have been instrumental in growing communities of AI researchers and developers within Africa and Latin America by hosting conferences and workshops and helping build local expertise in emerging technology. Many of these issues were recently raised in a Brookings webinar that included leaders from civil society organizations in the Global South, who helped to frame productive dialogues around these and other issues. As calls for localized development of AI systems increase, these organizations will become even more critical in ensuring that AI development meets the needs and interests of local communities.

Large tech companies have continued to expand their footprint in the Global South by establishing research labs, development centers, and engineering offices. IBM was one of the first big tech companies to establish an industry research lab in the Global South, building IBM Research India in 1998. Since then, IBM has launched research labs in So Paulo and Rio de Janeiro (2010), Nairobi (2013), and Johannesburg (2016). India has continued to be a market entry point for big tech research labs in the Global South, with Microsoft opening Microsoft Research India in Bangalore in 2005. Microsoft has continued to expand its reach, opening its Africa Development Center with two locations in Nairobi and Lagos in 2019 and launching the Microsoft Africa Research Institute, also in Nairobi in 2020. Google has also built up its research presence in the Global South, launching an AI research lab in Accra in 2018 and Bangalore in 2019. While developing research labs in the Global South is one step in advancing progress within AI, it is also important to understand that there is significant infrastructure and human capital necessary to maintain these labs and develop broader AI ecosystems.

Challenges of AI in the Global South

Despite the opportunities presented by AI, several challenges remain. Infrastructure challenges plaguing countries in the Global South could potentially hinder the development of AI in these regions with the large amounts of data needed to train AI systems and the high number of computing resources consumed in this process. Africa particularly struggles with internet access. In the last decade, internet penetration in Africa rose significantly, increasing from eight percent in 2011 to 36% in 2021. Limited internet penetration within Africa can largely be attributed to inadequate access to electricity and insufficient investments in crucial internet infrastructure components such as fiber optic cables, cellular towers, and base stations. According to data from the World Bank, 80.7% of the urban population in Sub-Saharan Africa is connected to electricity. Comparatively, South Asia has an urban electricity connectivity rate of 99.9, and Latin America and the Caribbean have a rate of 99.5%. This figure drops to 30.4% in rural Sub-Saharan Africa, compared to 98.3% in rural South Asia and 96.5% in rural Latin America and the Caribbean.

Concerns regarding the negative impacts of AI have led to a wide array of conversations regarding its use in domains such as healthcare, employment, and policing. However, many of these concerns have primarily been concentrated on the West, excluding perspectives on how AI may affect countries in the Global South. The Global South has also routinely become a destination for outsourced data labeling labor, with companies, such as Sama and Scale AI, relying on workers from this region. Recent coverage has highlighted the harms data workers and content moderators in East Africa and South Asia have faced when exposed to graphic content. And there are concerns that this exploitation could continue or even worsen. The lack of robust data protection and AI policies in the Global South could potentially lead to greater levels of misuse as AI grows in reach. Given that AI legislation is still in early development globally, there is an opportunity for countries in the Global South to circumvent the potential negative impacts of AI. To counter these harms, governments representing these countries must make a concerted effort to draft AI strategies and move towards enactment to protect vulnerable communities and enable responsible innovation. They must also be prominently represented at the table in multilateral global conversations on AI.

The road forward for AI in the Global South

The World Banks estimations indicate that connecting the 100 million Africans residing in remote areas would necessitate an investment of at least $100 billion. Plans are underway to improve connectivity in the Global South, starting with the African continent. 2Africa, the longest subsea internet cable ever designed, is currently under deployment and has 46 connections to land-based networks around 33 countries within Africa, Asia, and Europe. While most of the worlds estimated 485 in-service subsea internet cables are owned by large telecommunication companies, big tech companies that include Amazon, Google, Meta, and Microsoft have increased their subsea development efforts, currently owning or co-owning around 30 cables, with many more in development. However, this growing interest comes with concerns around algorithmic colonization and the potential for the interests of large companies to override those of local communities who may negatively bear the brunt of harm imposed by technical systems.

As countries in the Global South begin to build their respective AI capabilities, investing in cloud computing infrastructure independent of external platforms such as AWS, Google Cloud, or Microsoft Azure can help manage high computing costs and ensure that data is stored in compliance with local laws and regulations. However, there will also be a need for governments to invest in building data and cloud computing centers and training the necessary personnel to maintain them.

Governments in the Global South must also build the capacity to train local researchers and developers to help expand their respective AI ecosystems. Since AI research and development has traditionally been concentrated in Western countries such as the United States, Canada, and the United Kingdom, much effort is needed to close this gap. Forging partnerships with external entities can help countries in the Global South speed up the progress of building local AI capacity. Countries such as Nigeria have established partnerships with Microsoft to help equip citizens with digital skills, while other efforts from Google have trained nearly eight million people in Latin America in digital skills since 2017. However, given the unstable political environments and economies in some regions of the Global South, these efforts could be hampered if brain drain continues to increase. It is essential that as AI talent is trained within these countries, they are encouraged to stay and contribute to local economies. It will also be vital that countries in the Global South build their respective AI capabilities by supporting the creation and maintenance of thriving AI ecosystems that promote entrepreneurship and support local innovation through research labs and digital hubs.

Additionally, governments in the Global South should integrate digital skills training into primary and secondary school curricula help build a pipeline of researchers and developers in emerging technologies. Some early efforts have been seen in Kenya, where the governments Digital Economy Blueprint focuses on to incorporating topics in computer literacy, ICT skills, coding, digital citizenship, and online safety into K-12 curriculum. Within the rest of the Global South, plans to implement educational upskilling have been noted in digital transformation initiatives from Brazil, Costa Rica, India, Jamaica, Malaysia, Panama, Rwanda, and South Africa. However, given that many of these plans to improve digital skills training are still in development or early stages of implementation, there is much work to do to realize the potential of sustainable AI workforces in the Global South.

Finally, AI can deliver many other opportunities for countries in the Global South, ranging from more streamlined healthcare systems, improved access to education, and expanded economic growth. PwC estimates that AI could contribute up to $15.7 trillion to the global economy by 2030. However, excluding China, only $1.7 trillion of this economic impact is expected to impact the Global South. This outlook is concerning given that the Global South holds a majority of the worlds population, potentially limiting the economic advantages of AI to those already reaping the benefits of emerging technologies. Cautious approaches to building, implementing, and governing these technologies are needed. AI should not be seen as a panacea for solving development issues. There should be equitable investment by countries toward building capacity for traditional social services while making efforts toward building sustainable AI ecosystems. To work towards these goals, countries in the Global South should continue participating in international collaboration and partnerships and leverage existing expertise within their respective countries. The ability of the Global South to innovate despite existing challenges will help define the role of the global majority as the world transitions into a digital future which AI stands to inevitably shape.

Continue reading here:
AI in the Global South: Opportunities and challenges towards more ... - Brookings Institution

Governor's Office

TAIPEI, Taiwan Governor Greg Gianforte today met with President Tsai Ing-wen of Taiwan to strengthen Montanas relationship with its longstanding partner and ally.

Montana and Taiwan share nearly four decades of history as trading partners and friends, built on our common values of individual liberty, innovation, and free enterprise, Gov. Gianforte said. It was an honor to meet with President Tsai this morning to convey our appreciation for this longstanding partnership and our optimism for the future.

Governor Gianforte meeting with President Tsai of Taiwan

President Tsai hosted Gov. Gianforte at the Presidential Office Building in Taipei for the meeting.

I would like to begin by welcoming Governor Gianforte as he leads this economic and trade delegation. On behalf of the people of Taiwan, I extend our sincere gratitude to him for making Taiwan the first stop of his trip. I am also grateful to Governor Gianforte for reopening the State of Montana Asia Trade Office-Taiwan after taking office in 2021 to continue strengthening bilateral economic and trade cooperation through concrete action, President Tsai said.

President Tsai continued, Since taking office, Governor Gianforte has also been keen to promote tax incentive and deregulation legislation. This has created more job opportunities and enhanced the investment climate.

During the meeting, the governor and president reflected on Montana and Taiwans sister state relationship and discussed opportunities for economic collaboration.

Below is a transcript of President Tsai's remarks, translated:

I would like to begin by welcoming Governor Gianforte as he leads this economic and trade delegation. On behalf of the people of Taiwan, I extend our sincere gratitude to him for making Taiwan the first stop of his trip. I am also grateful to Governor Gianforte for reopening the State of Montana Asia Trade Office-Taiwan after taking office in 2021 to continue strengthening bilateral economic and trade cooperation through concrete action.

Taiwan and Montana have long enjoyed close cooperation in agriculture and tourism. Large numbers of Taiwanese tourists visit such famous attractions as Yellowstone National Park, and agricultural goods from Montana such as beef and wheat are very popular among domestic consumers.

Montana also boasts key US industry clusters in the photonics, optoelectronics, and optics sectors, and is actively developing its biotechnology, cloud computing, and aerospace industries. Since taking office, Governor Gianforte has also been keen to promote tax incentive and deregulation legislation. This has created more job opportunities and enhanced the investment climate.

Taiwan is Montana's seventh-largest trade partner. As the bilateral trade environment becomes even more favorable, Taiwan and Montana can continue to deepen partnerships in such key industries as photonics, optoelectronics, optics, and semiconductors to foster mutually beneficial development.

Taiwan and Montana also share the values of freedom and democracy. I want to thank Governor Gianforte, as well as the Montana Senate and House of Representatives, for passing Taiwan-friendly resolutions supporting our international participation. Taiwan will deepen collaboration with even more like-minded democratic partners to jointly address global challenges.

This delegation led by Governor Gianforte is a key step toward bolstering bilateral relations. We anticipate that, through the efforts of both sides, Taiwan and Montana will enjoy even broader and more far-reaching exchanges going forward.

And below is a transcript of Governor Gianfortes remarks:

President Tsai, thank you for taking the time to meet with us. It's an honor to be in Taiwan with you today. Beginning in 1985, with the signing of our sister state relationship, Montana has shared a strong bond with Taiwan. This bond has been forged through trade and educational exchanges and our shared values of freedom and free enterprise.

As you mentioned, our legislature in Montana reinforces this bond every two years with a joint resolution in support of Taiwan. In honoring that partnership, I proudly reopened the Montana Asian trade office in the heart of Taipei during my first year in office, ushering in new opportunities for the people of Taiwan and Montana. And now two years later, it's only fitting that I lead my first international trade mission as governor to this great country.

Montana is best known around the world for our beautiful vistas and wide-open spaces. Yellowstone and Glacier National Parks are both right in our backyard and we see millions of visitors every year. While our wide-open spaces are admired for their beauty, they also create excellent conditions for growing wheat and raising beef. Just a four-hour drive, north of Yellowstone National Park sits Montana's Golden Triangle. There our farmers seed more than two million acres of wheat each year. Hot days and cool nights in the summer make for some of the finest wheat in the world. Earlier this year, we were honored to host a delegation of flour millers in Montana to showcase where and how we grow these crops.

While agriculture surely remains the bedrock of our trade relationship with Taiwan, we're also seeing rapid growth in other industries like education, bioscience, and photonics.

The Ministry of Foreign Affairs and the Ministry of Education have been funding two programs within the state of Montana. One, housed at the University of Montana within the Mansfield Center, will begin early next year and is dedicated to growing the Mandarin program for both high school and college students in Montana. The second, at Montana Tech and Minghsin University of Science and Technology, will focus on short-term exchanges related to international business particularly as it relates to the semiconductor workforce. Globally, it's expected that education will be a $7 trillion industry by 2025. Montana would like to be part of this, and our universities have set forth a serious agenda to create more connections internationally.

Montana ranks sixth nationally among states for bioscience industry growth over the last five years and fifth in the United States for growth in research and development. This means our bioscience industry is expanding and we're at the tip of the spear for cutting-edge research.

Montana also has one of the highest per capita concentrations of optics, photonics, and quantum computing companies in the United States. The 21st century will depend on photonics as much as the 20th century depended on electronics. Globally the photonics industry is expected to grow from $1.5 trillion to nearly $2 trillion by 2025. It is imperative that we've worked to build this industry for our state, and Taiwan is a key partner in this.

During our visit here to Taipei, we will sign a memorandum of understanding with the Taiwan-USA Industrial Cooperation Promotion Office and the Taiwan Photonics Industry and Technology Development Association to continue discussions and relationships begun by our state office.

I speak on behalf of our entire delegation, Madam President, when I say I'm filled with optimism. Optimism about the future of Montana and Taiwan, and excited about the possible extensions of our partnership. Again, on behalf of the first lady and myself, thank you for hosting us today.

Later, the governor joined members of the delegation for an appreciation luncheon with Taiwans Deputy Minister of Foreign Affairs Roy Chun Lee, who supported Montanas trade mission.

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Originally posted here:
Governor Gianforte Meets with President Tsai of Taiwan - the State of Montana NewsRoom

Oct 30, 2023The Hacker NewsWebinar / Web App Security

Modern web app development relies on cloud infrastructure and containerization. These technologies scale on demand, handling millions of daily file transfers it's almost impossible to imagine a world without them. However, they also introduce multiple attack vectors that exploit file uploads when working with public clouds, vulnerabilities in containers hosting web applications, and many other persistent threats.

We surveyed organizations responsible for securing critical web applications used by healthcare, financial services, technology, and other critical infrastructure verticals to learn how they tackle the most destructive threats and summarized our findings in the OPSWAT 2023 State of Web Application Security Report. The survey report revealed that:

In this webinar, join our panel of web application security experts as they expand on the insights gathered while protecting the world's most critical applications.

Our experts will also share five must-know web application security insights, including:

Platforms like Microsoft Azure, Amazon Web Services, and Google Cloud Platform are ubiquitous for hosting web applications. However, embracing public cloud hosting without implementing the requisite security measures exposes applications to data breaches.

Despite significant advantages, containers may bring additional security risks. Malware or vulnerabilities hidden in containers hosting web applications can disrupt business, risk customer data, and lead to compliance violations.

You must check files for malware and sensitive data to prevent breaches and ensure compliance. Our panel will outline pitfalls and tools you can use to avoid costly and embarrassing data leaks.

Organizations must implement automated tools, services, and standards that enable teams to securely develop, secure, deploy, and operate applications.

Despite most organizations increasing their security budgets, most only use five or fewer AV engines to detect malicious files. Surprisingly, very few disarm files with potentially dangerous payloads with Content Disarm and Reconstruction (CDR) technology.

Join our panel of cybersecurity veterans Emo Gokay, Multi-Cloud Security Engineer at EY Technologies and George Prichici, VP of Products at OPSWAT, as they share insights and strategies gathered from the frontlines of securing critical infrastructure from advanced and persistent malware.

Register now to walk away with five key web application security insights and strategies.

More:
New Webinar: 5 Must-Know Trends Impacting AppSec - The Hacker News

Ansible and Docker are popular tools for organizations looking to accelerate software releases via automation. While these tools couldn't be more different, they can work well together -- each accomplishing a different, important task for deploying and running software.

Docker enables you to run an application in a maintainable and repeatable manner. An admin can write a Dockerfile that stores all an application's commands and then build a Docker image and run it on most systems.

With Ansible's automation capabilities, admins can easily provision and configure servers. Ansible is developed in Python and can run on most machines to install updates to dependencies, configure software or orchestrate running applications.

Let's explore Ansible and Docker to see how these tools differ and how they can work together.

Supported by all cloud providers, Docker is often the path of least resistance for the deployment of an application to the cloud. Advantages include the ability to quickly get new containers up and running, the portability of a Docker image and the benefits of turning an application's environment configuration into a Dockerfile.

A Docker container doesn't load an OS, which means it can start running in seconds. Applications can scale quickly as well -- simply spin up more containers using Docker deployment tools, such as AWS Fargate, Google Cloud Run or Azure Container Instances. It's also possible to switch an app between cloud providers or even host the app on premises because Docker containers are easy to configure in cloud-hosted and local environments.

If you work with a Docker image, then your application's deployment is contained in a Dockerfile. A Dockerfile is written with commands to configure the application's running environment within the Docker container. Examples of simple commands in the Dockerfile include the COPY command and ENTRYPOINT command. The COPY command copies the application's executable file into the Docker container, while the ENTRYPOINT command runs the executable as the container's main process.

Since these configurations are captured in code, they can be kept in a version control repository. GitHub, for example, maintains a history of all the changes to the application's Dockerfile. This enables developers to collaboratively maintain the application's running environment.

Enabling developers to create and maintain their application's running environment is critical to a team's DevOps efforts, which aim to break down the barrier between writing application code and running and operating an application.

Ansible automates processes, which can help organizations improve a wide range of efficiencies. For IT tasks, such as the management of developer machines, Ansible makes it possible to create and maintain the setup of a developer's machine in code.

To do this, Ansible uses playbooks, which contain plays. A play is the basic unit of Ansible execution and contains variables, roles and an ordered list of tasks that can repeatedly be run. For example, a play can contain the necessary steps to install and configure a custom Secure Sockets Layer/Transport Layer Security certification and be executable on any machine Secure Socket Shell can access.

A playbook could also provision a server to run an application. The benefits of using Ansible, much like Docker, are that containing these configurations in code provides a working history of changes.

It's possible to use Ansible with Docker to manage more infrastructure. Docker containers offer a way to efficiently build an application, but they require a service to handle their configuration, deployment and orchestration. Ansible is useful for this -- an Ansible playbook can install and configure Docker on the host machine, install a Docker image and run that image as a service.

Cost and customization are the advantages of controlling an application's Docker runtime setup and configuration. Other container tools, such as Fargate, are more costly than running a basic server on premises. When you create your own Ansible playbooks, you also get fuller configurability.

Ansible has a huge advantage over provisioning machines by hand for organizations that don't run applications in the cloud. Using cloud-based tools, such as Fargate, can be compelling, but Ansible and Docker can provide a company with complete control of the server on which their application runs.

Here is the original post:
Compare Ansible vs. Docker use cases and combinations - TechTarget

User dissatisfaction with IT asset management stems largely from the difficulties associated with identifying and tracking assets that aren't subject to central procurement or readily available for physical inventory. Most cloud users know these challenges exist for cloud assets, as well.

Many cloud services reduce the ability of central asset management to see all the assets that support cloud connection and use. This obscurity leads to a key principle of cloud asset management: Traditional asset tracking must be magnified and enhanced for cloud use.

The general goals of IT asset management (ITAM) systems include the following:

Utilization efficiency has increasingly broadened to include cost management versus quality of experience, which links asset management to performance. This shift is particularly important for cloud assets because of their elastic -- and somewhat ephemeral -- nature. However, the performance efficiency of cloud assets demands a new look at asset tracking.

It's possible for midsize companies to use simple tools, such as a desktop spreadsheet or database program, to organize ITAM data if their assets are on premises. However, that approach is problematic for cloud assets because of their ephemeral nature. Companies need to be able to discover assets from logs, which often contain too many transcription errors.

No matter what tools enterprises use, the right approach to cloud asset management is essential for optimized performance.

Enterprises can't tag a cloud asset, inspect it for inventory or read serial numbers. But cloud assets dependably come with bills. Cloud asset management starts with the centralized collection of all cloud billing.

Remove charges for management features and other non-hosting elements. Leave charges for hosting application components or databases, as well as cloud feature usage directly linked to these elements. This set of charges is the baseline for cloud asset management, so it's important to capture the explicit resource name and code, the nature of the resource, and the organization and individual responsible for ordering it.

The next step is primary governance and security screening of cloud assets. Companies should validate the features of all cloud services against their security and governance policies to ensure the services don't contain features that could compromise policies.

If enterprises haven't done this step already, they should perform it before undertaking other cloud asset management tasks. At this point, the goal is to assess the services against general governance and security policies. Address application-specific issues later, as described below.

While cloud teams can audit cloud costs now, it's probably better to do so when it's possible to make associations between billed costs and applications.

Next, associate cloud assets with application deployments. This step is particularly important for performance optimization.

A bill records the use of a cloud asset, while a log records the user. In some cases, cloud deployment tool logs and scripts -- such as Kubernetes and DevOps -- might be required to link application components to specific cloud assets and their costs. This association helps assess how resources are actually used, as it links them to specific applications and users. That association then links cloud usage monitoring with application performance monitoring (APM).

For the remainder of cloud asset management processes, the application link to the cloud establishes tracking and performance baselines.

The log connection is the basis for managing licenses and application costs. For each application license, the link to cloud resources and assets indicates a use or deployment that might then be regulated under software license terms. This applies not only to applications but to any middleware customers deploy in the cloud.

AI is a technology, not a goal, so it's critical to ensure that the selected tools fit the mission optimally.

At this stage, enterprises should conduct application-specific security and governance reviews, as connections between cloud assets and applications are now auditable. It's also practical to assess the pricing and billing policies now, because the link to the application is a link to the business case that justifies it.

In hybrid cloud applications, this step reveals a link between the cloud and data center for specific applications. That then requires cloud asset management practices to interlock with ITAM practices to gain complete asset visibility.

Performance optimization requires enterprises to assess cloud resource costs versus application performance levels. This step requires time-correlation of billing for cloud resources and application performance levels. Teams can derive the former from the cloud bill-to-application associations and the latter from APM tools. If ITAM procedures manage data center assets, that data can be correlated with cloud data via the common application linkage.

This is a monitoring and data analysis/correlation task, with the aim to augment traditional cloud logging and APM tools with AI tools for analysis. AI is a technology, not a goal, so it's critical to ensure that the selected tools fit the mission optimally.

The cloud is a target of performance analysis, so it could be a candidate for hosting some or all components of asset management. This approach has its benefits and challenges, beyond the traditional ones of comparing cost and features with what's available for use on premises.

Cloud tools often fit the cloud provider who offers them, but they're more difficult to adapt to other multi-cloud or hybrid cloud environments. This point is particularly important for asset management applications but is often missed when enterprises consider options.

No single tool can fit a typical enterprise's cloud asset management challenge. A combination of tools and strong procedural controls is essential. Relying on a tool or tools without those controls is almost surely going to lead to performance, cost and governance problems.

Link:
5 cloud asset management best practices to optimize performance - TechTarget