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What Is Vector Similarity Search?
Posted in: AI, AI-driven data analytics, Big Data, cybersecurity, data searches, machine learning, machine learning algorithms, News & Trends - Aug 11, 2021Regardless of your industry, you probably know that staying abreast of new technologies is an important part of keeping a company competitive and able to meet emerging needs. Vector similarity search is a relatively new option that could soon become more relevant for businesses. Here’s what you need to know about it.
What Is Vector Similarity Search?
As you might guess from its name, a vector search involves representing pictures or bits of text as vectors, or embeddings. They often help train machine learning models. Object similarity also comes into play, which compares the vectors in a multidimensional space.
A vector search involves representing pictures or bits of text as vectors, or embeddings.
Closeness represents more vector similarity between the embeddings, whereas more distance means fewer common characteristics. People using a vector search engine could perform nearest-neighbor searches to determine the closest query-related vectors in a space.
How Could Businesses Use Vector Similarity Search?
A vector search uses deep learning and other advanced techniques to answer queries based on contextual understanding rather than a simplistic assessment. Here are some specific ways your organization could see the advantages of vector similarity searches.
Show Users Similar Products
Giving e-commerce site visitors similar or exact matches to the things they search for is crucial for prolonging their engagement and increasing the likelihood of a sale. The results of a vector search could be useful for showing shoppers such content.
eBay developed an interactive visual search feature based on the vector similarity approach. Users choose pictures from batches of images that most closely match the products they want. People see new groups after making their selections.
The idea is to gradually narrow down the online marketplace’s massive product assortment while encouraging item discovery.
Develop Deep Learning Algorithms More Quickly
Vector similarity search relies on deep learning — an advanced form of artificial intelligence (AI) based on how human brains process information. There’s a growing push for businesses of all types to see how AI could help them.
For example, statistics show it’s possible to get up to 20% conversion cost reductions when applying AI to core business practices in producing industries, according to BlueSentry. However, many companies don’t have people on their teams with extensive AI knowledge, and it’s not always easy to find such specialists quickly.
That said, a company called SentiSight.ai offers an online dashboard geared toward people who want to develop similarity search models, but don’t have extensive prior knowledge.
For example, the product’s image similarity search function can make predictions about pictures a person uploads from their mobile phone. There’s also an AI-assisted labeling feature.
Read more: AI Software Trends for 2021
Improve Security Measures
Maintaining a high level of physical and cybersecurity is vital for today’s businesses to succeed. For example, vandalism or product theft could cut into profits, while a ransomware attack could lock company representatives out of critical systems and data.
A recent study found that one in three organizations are experiencing more cybersecurity attacks this year than last. Fortunately, vector similarity approaches could help in both regards.
A vector search engine could store data about people who have stolen from a store previously, allowing an algorithm to recognize possible problematic shoppers. Computer codes could also feature in vector similarity searches. According to GSI Technology, checking a piece of software against a database of known vulnerabilities could tell a company whether the product has issues for hackers to exploit.
Read more: What Is Adversarial Machine Learning?
Improve SEO Strategies
You may also use a vector search within a search engine optimization (SEO) strategy. That’s because it can help you find word synonyms that could help you include phrases relevant to customers’ primary search terms.
For example, Word2Vec finds the words most similar to an originally inputted one. It works with pieces of text and assigns one vector to each word. The closest vectors represent the best-matching terms.
Read more: AI vs. Machine Learning: Their Differences and Impacts
What Could Negatively Affect Widespread Adoption?
Now that you know why company representatives might use a vector search engine strategy in their operations, you might wonder why this technology is not yet part of the mainstream. The main challenge is that vector similarity search is still emerging.
It may not be easy to convince decision-makers to invest in a technology that does not have widespread usage.
Thus, it may not be easy to convince decision-makers to invest in a technology that does not yet have widespread usage. Business leaders often want to see case studies before committing to investments, and it’ll take a while to gather the evidence for those.
Further, vector similarity databases once required significant resources to implement and maintain. However, service providers are making it easier to work with these searches at modest costs. For example, Pinecone offers a fully managed vector similarity search database and a pay-for-what-you-use model.
How Can You Explore Vector Similarity Search Applications?
If you’ve decided to dive into vector similarity search and determine some of the specific ways it could help your business, there are a few options beyond those already mentioned.
Facebook’s engineers unveiled Faiss, a vector similarity search tool, in 2017. Developers reported an 8.5x improvement in processing time when using it across GPUs for nearest-neighbor searches. You can get it on GitHub. However, it’s intended for people with prior coding experience.
There’s also Weaviate, an open-source tool that allows working with any kind of media — including video, audio and text. Milvus is an open-source vector search engine suited to unstructured data, and counts Trend Micro and the Cleveland Museum of Art among its users.
Microsoft offers Bing vector search, another specific tool geared toward developers. And companies in the AWS ecosystem can leverage Amazon SageMaker and Amazon ES to build visual search applications.
Will You Benefit From Vector Search?
This technology is still in the very early stages. As more companies decide to use it, the potential applications will become even more evident and exciting.
If you’re strongly considering using vector search based on what you’ve read here and elsewhere, start by envisioning a few business cases or goals you want to meet. Then, research more deeply into how vector similarity searches could provide the necessary assistance.
Read next: Top Big Data Tools & Software for 2021
The post What Is Vector Similarity Search? appeared first on CIO Insight.
topEdge Computing: Tips for Hiring and Getting Hired
Posted in: Big Data, Careers, CISSP, cybersecurity, data science, DevOps, diversity hiring, edge computing, Hiring, hiring best practices, Innovation, IT job market, IT Strategy, job search, Leadership, maintenance, News & Trends, Project Management, Workplace - Aug 11, 2021As more users gain access to technologies like IoT devices and smart applications, enterprises are quickly discovering the importance of developing edge computing infrastructure and capabilities. According to a study from Grand View Research, the edge computing market is expected to grow significantly from its 2020 value of $4.68 billion, reaching approximately $61.14 billion by 2028.
The edge computing hiring market is necessarily growing at a rapid pace, in order to keep up with both innovation and maintenance needs for edge technology. Whether you’re looking to hire an edge computing expert or you’re interested in getting hired in this field, data and cybersecurity best practices can prepare you for success in edge computing.
Getting started in an IT career: What Are CIOs Looking for in Current IT Grads?
The Edge Computing Job Market
What is Edge Computing?
Edge computing is the practice of managing and processing data “at the edge” of the network, or near the site of the edge device. Edge technology works through edge sensors, which are distributed more widely than traditional cloud and on-premise setups. Many edge devices and applications are also designed with the ability to process data themselves.
By bringing computing actions closer to the user, edge technology improves latency. It also decreases the chances of downtime, and can even reduce bandwidth costs through minimal data transmission.
Learn more: The Pros and Cons of Edge Computing
Tips for Edge Computing Recruiters
CIOs and tech recruiters should look for edge computing candidates who exhibit typical IT skill sets and experience. They should specifically demonstrate knowledge or certifications in cybersecurity, application development, and the latest happenings in the industry. But many recruiters fail to consider the following hiring needs when they’re searching for edge computing employees.
Don’t Forget About Maintenance Hiring
Brainstorming and building edge technology is always the first step, so it makes sense to hire individuals who can develop the tech. But many organizations overlook the importance of hiring for edge monitoring and maintenance as well.
Edge devices, sensors, and networks are widespread and can be found in the possession of virtually anyone. As such, it’s important for security and maintenance infrastructure to be established and for employees to know how to manage it. Without frequent upgrades and monitoring, edge tools cannot work to their full potential.
Ask interviewees problem-solution questions to see how they would solve common problems your organization faces with edge technology. To really understand their analytical thought process, specifically ask how they would handle business edge problems versus consumer edge problems.
Ask Questions About Ethical Tech Experience
Edge computing, IoT devices, artificial intelligence, and machine learning have all quickly snuck into mainstream technology pools. These tools enable businesses to glean greater data intelligence and automation opportunities, as well as personalize customer experiences.
However, they also present businesses with more personal and highly sensitive data than ever before. Maintaining and developing edge technology is a huge responsibility in the modern world and requires superior ethics to ensure tools are developed with all users in mind and data is used responsibly.
Hire individuals from diverse cultural, socioeconomic, and educational backgrounds so they can offer a fresh, more user-centric perspective on how these tools should work, and where they should be deployed. At the very least, ask candidates questions to gauge their cultural awareness and ability to build tech that empowers and protects personally identifiable information.
More on ethical technology practices: AI Software Trends for 2021
Look for Potential Everywhere
Edge sensors and devices are found virtually everywhere, so companies need to start looking beyond traditional tech hubs when hiring. Edge computing makes many life-changing solutions possible, such as offering robotic surgeries and self-driving cars with real-time efficiencies. But for edge computing to truly be life-changing, edge technology must be made fully available everywhere — even in rural and impoverished areas.
Look for hiring potential in less techy areas of the country and the world, because you’ll need maintenance technicians and edge experts to build up this infrastructure everywhere. With the growth of remote work and many tech companies moving their headquarters and satellites to new locations, you’ll likely find eligible candidates no matter where you look.
Tips for Edge Computing Applicants
Invest in Data Science Education and Knowledge
Many people underestimate the importance of data quality knowledge and skills. Data quality best practices make it possible for edge computing devices to receive appropriate information in real time. This improves data commands and ensures unnecessary data doesn’t hurt operational speed.
Since edge tech moves so quickly, it’s more difficult and even more crucial for experts to double-check data sets for technical and legal compliance. To make yourself stand out as an edge computing candidate, make sure you know data science best practices and data quality standards. Also consider finding a relevant data management certification.
More on data science: 9 Key Considerations When Building a Global Data Science Team
Build Up Your Cybersecurity Skills
Monitoring edge devices and security is more difficult than more centralized data center and cloud monitoring, but that difficulty makes it all the more important for candidates to demonstrate strong cybersecurity skills. Study computer science in college, or find extracurricular resources and certifications to familiarize yourself with important cybersecurity concepts and skills.
Some certifications for building up your expert skills for edge careers include:
- Certified Information Systems Security Professional (CISSP)
- Platform and vendor-specific certifications (example: the AWS Snowcone certification)
- Edge computing introductory courses from Coursera, Udemy, and LinkedIn Learning
Read more: What Is Enterprise Security Management?
Get to Know DevOps Principles
Many companies hiring for edge tech and other trending tech movements are moving toward a DevOps approach. This project management and software development technique focuses on regular, iterant communication and teamwork between development and operations teams.
If you are a new graduate or are unfamiliar with the DevOps model, you won’t necessarily be able to demonstrate your knowledge of how DevOps works. But in the interview process, be sure to emphasize your ability to work in hybrid team settings. Give examples of how you’ve worked on tight, sprint-style deadlines in the past. Though not every edge provider has moved to the DevOps approach, many are developing new technology quickly and appreciate candidates who can move efficiently and take feedback from different sides of an organization.
More on DevOps: Best DevOps Tools & Software of 2021
The post Edge Computing: Tips for Hiring and Getting Hired appeared first on CIO Insight.
topBest Practices for Plan-Build-Run Model
Posted in: agility, Application Development, best practices, Innovation, IT costs, IT framework, Leadership, Plan/Build/Run, ROI - Aug 09, 2021The IT industry has recently seen an uptick in enterprises pursuing the process-centric plan-build-run model within IT, rather than a traditional tower based model. However, many CIOs are struggling with proper execution and design.
Effectively driving change in IT to meet business needs, while sustaining a highly reliable set of platforms on which to run the business, may best be served by a process-centric model — but it must be executed well.
Read more: What Does Digital Transformation Mean for IT?
What Is the Plan-Build-Run Framework?
The plan-build-run (PBR) model divides IT into three units. The plan unit is responsible for strategy and roadmapping, taking on tasks like enterprise architecture and demand management. The run unit is focused on maintenance. Finally, the build unit handles project and program management, as well as new development.
IT must carefully approach the PBR framework and apply best practices to ensure successful results.
The model itself is particularly relevant, as IT organizations acquire services in new and agile ways, such as SaaS. The traditional tower designs focused on infrastructure, applications, and more become much less effective at meeting the business’ demand for change and agility.
The traditional tower model also complicates accountability in effectively managing suppliers that deliver services that substantially crossover the traditional IT towers of applications and infrastructure. IT organizations must carefully approach the PBR framework and apply best practices to ensure successful results.
Best Practices for Plan-Build-Run Model
Organize With Accountability
Create organizational units that have distinct accountability for plan-build-run. This provides clarity in process ownership and responsibility for outcomes.
Leverage Business Analysts
Create a strong corps of business analysts and solution architects who align with the business relations team to support upfront planning. However, don’t align business analysts with the application teams.
They need to drive functional knowledge of business processes into the initial scoping effort, clarifying the needs for change in the application landscape. They will optimize the change needed within the application by driving consistent business processes. This approach reduces time to market, as well as total cost of ownership.
Read more: Analysts Forecasting a Bright Future for IT Spending
Introduce Service Portfolios
Create service portfolios supported by solution architects within the Plan function that retain end-to-end visibility of the cost and value of those services, as well as the ability to assess and plan the demand for change within that portfolio.
The portfolio leaders will drive efficient utilization and rationalization of the application suite, as well as retirement and migration of less used or expensive-to-maintain applications and platforms. This drives optimal cost, increases value and reduces the IT portfolio’s complexity.
Create Enabling Financial Protocols
Create a financial mechanism that enables expenditure of adequate resources in early planning and scoping and doesn’t hinder or hurry valuable planning work because of an expectation of project-based chargeability.
The early project phases of scoping and planning are critical to the creation of a valid business case. They are not only valuable in assuring that investments are targeted correctly, but they result in substantially improved estimates and more on-time delivery. This practice optimizes investment expenditure and drives value realization to achieve strategic business objectives.
Give Decision-Making Power to Planning
Shift the power in decision-making away from the application leadership within IT, which is the traditional center of decisions on meeting new demands, and toward a planning function that is integrated with enterprise architecture.
Shift the power in decision-making away from the application leadership within IT.
The power shift drives platform rationalization and consolidation, not the constant expansion of the IT application portfolio. This approach reduces implementation and support costs while increasing the speed and quality with which change can be delivered.
Use Portfolio Planning to Prioritize
Leverage the portfolio planning function to prioritize and sequence demand while balancing capacity. Start projects once they are sufficiently planned and adequately resourced, or they will simply end up “red” from the outset.
Without an understanding of the portfolio and capacity constraints, executives and other leaders could step in to drive determination of a budget and timeline that may or may not be achievable. With proper prioritization, IT can ensure transparency and visibility for better decision-making.
Establish Architecture Depth
Create sufficient architecture capability to enable early engagement to assure alignment with long-term IT goals of reducing total cost of ownership, long-term support costs, and landscape complexity. This allows the technology portfolio to be more responsive to business needs, easily modified, integrated and supported.
Read more: Top Big Data Tools & Software for 2021
Don’t Proceed Until Ready
Put into production only that change which is ready to be supported. The effectiveness of the PBR model is dependent on teams staying in their lanes, and to do that, the run team needs to be ready to take the baton. That doesn’t mean they need to do a better job of getting ready; instead, it means “Build” needs to make sure “Run” gets what they need.
Above all else, the success of any model is dependent on the ability of leaders to provide a cohesive and consistent vision to their teams of how work gets done. It requires accountability and ownership, as well as transparency, great communication and teamwork.
With those components and the above nine best practices in place, the plan-build-run framework can put IT teams ahead of the curve in delivering effective programs in today’s ever-competitive business environment.
The post Best Practices for Plan-Build-Run Model appeared first on CIO Insight.
topCloud Cost Management: Tips & Best Practices
Posted in: cloud, cloud costs, cloud management, cloud management service, Cloud Virtualization - Aug 09, 2021Today, most businesses have some or all of their data stored on the cloud. Now that so many companies have adopted this strategy, many want to know: how can a company find optimal and efficient ways to manage cloud costs and cloud services?
Getting the most out of cloud cost management, cloud tools, and best practices often means outsourcing cloud costs and IT teams for most companies. Outsourcing these expenditures can help any firm manage its bottom line.
Table of Contents
- What Is Cloud Cost Management?
- Is Cloud Cost Important for Businesses?
- Outsourcing Cloud Cost Management
- What if a Company Has Multiple Clouds?
- Public Cloud Providers
- Is Cloud Spending Increasing?
What Is Cloud Cost Management?
Cloud cost management helps businesses understand and manage costs based on their individual cloud technology needs. Many contributing factors can affect cloud costs, including memory usage, storage, network traffic, usage of web services, and things like IT personnel and software licenses.
Therefore, a cloud cost management strategy will typically take these factors into account.
Read more: How to Tailor Security Frameworks to a Cloud-Based Infrastructure
Is Cloud Cost Important for Businesses?
Anything that can help a company control its spending while maximizing its resources is a benefit in both the short and long term. With cloud cost management, users can reduce unneeded spending while helping to plan for the future.
Keeping track of cloud costs can become complicated, and it’s easy for costs to become exorbitant — especially if the company pays based on its usage. So even if your company has strong IT, outsourcing cloud management could be the best solution for cloud cost management.
Outsourcing Cloud Cost Management
Outsourcing cloud costs can have many benefits for most businesses. When relying on an outsourced data facility with IT staff, almost any company will reduce its cloud cost expenses. That said, there are other reasons why an organization would want to rely on someone else for its cloud cost management best practices.
When a company outsources cloud costs, they can expect a few things:
Better Performance and IT Expertise
Experienced managed service providers work with companies to implement a customized cloud solution that fits business goals while ensuring updated compliance and security. If a company is small — or has a small IT staff — they may not know how to deliver and maintain cloud cost management best practices.
An outsourced cloud service provider offers expertise and reduced costs while planning, implementing, performing data migration, and regular maintenance.
Read more: SAP ERP Software: S/4HANA Cloud Review for 2021
Reduced Costs
An outsourced cloud system can help reduce in-house IT costs, allowing a business to focus more on IT strategy.
But a company can save on more than just IT costs. For example, the average lifespan of the computing equipment needed tends to be three to five years. That means a company will have to replace or upgrade costly equipment quite often.
In addition, the company will need to have experienced IT personnel, server admins, and engineers, all while paying for an on-site data center. As a result, a company can accrue unnecessary costs for data storage. Said data can be quickly moved to a cloud and, in turn, experience decreased upfront and future management costs.
Companies can drastically reduce their cloud cost management by relying on an outsourced staff and data facility.
Increased Security
A company needs to maintain cloud security while having the proper access to controls, real-time monitoring, and vulnerability management. If a company doesn’t specialize in IT, it’s more likely they will make mistakes that could lead to vulnerabilities.
With an outsourced cloud provider, a company doesn’t have to worry as much about personally dealing with hackers or other security breaches. In addition, any reputable cloud provider will have the ability to pass compliance audits, which can be costly for a company of any size to manage on its own.
If any general problems arise, the cloud company can usually handle them without a business dipping into its own resources.
What if a Company Has Multiple Clouds?
If your company uses multiple clouds, a multi-cloud management system is a set of tools that will help secure and monitor applications from across several public clouds.
According to Flexera, “92% of enterprises have a multi-cloud strategy; 82% have a hybrid cloud strategy, using both public and private clouds.”
More and more companies are seeing the benefit of a multi-cloud strategy, as they can pick and choose their services, tailoring them to fit their needs. A multi-cloud system also allows entities to choose where they will host these solutions.
Public Cloud Providers
Public cloud providers give a business the option to decide what resources fit their needs, and it’s no wonder public cloud adoption continues to accelerate.
For example, public clouds offer a company communication services. Providers like Google, AWS, and Azure provide the services needed to address peak demand, as well as perform IT and other business operations.
In general, an organization should choose a provider close to their office to improve network performance.
Is Cloud Spending Increasing?
In short, yes. According to Gartner, “Worldwide end-user spending on public cloud services is forecast to grow 23.1% in 2021 to total $332.3 billion, up from $270 billion in 2020.” In 2021, companies are seeing higher-than-expected cloud usage due to COVID-19, while most struggle to control their growing cloud spending.
The pandemic has accelerated spending as more businesses put more extensive workloads on the cloud. As the need for more virtual space increases, you can expect cloud management to keep growing in both size and importance.
Many factors contribute to cloud costs, and those factors are constantly shifting. However, managing cloud costs can be as simple as outsourcing an enterprise’s cloud cost management. By outsourcing, a business benefits from only paying for what they use, an expert IT staff, better performance, and increased security.
Read next: Cloud Spending to Power through 2021
The post Cloud Cost Management: Tips & Best Practices appeared first on CIO Insight.
top5 Things to Look for in Your Next Data Science Platform
Posted in: Business Intelligence - Aug 09, 2021Finding the right data science tools is paramount if your team is to discover business insight. Here are five things to look for when you search for your next data science platform. top
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