Techopedia Q&A

How is a finite state machine used in artificial intelligence?
Why is it important for data scientists to seek transparency?
Why is so much of machine learning behind the scenes - out of sight of the common user?
Why is Python so popular in machine learning?
What is 'precision and recall' in machine learning?
What are some of the biggest challenges with legacy migration?
Why are GPUs important for deep learning?
Why would companies invest in decision automation?
What is connective intelligence? What does it do? What role will it play in Web 3.0?
Who invented augmented reality?
How will Web 3.0 connect data better?
What’s a simple way to describe bias and variance in machine learning?
How has cyber threat intelligence evolved over the last few years and where is it headed?
What are some of the main benefits of ensemble learning?
What does a threat intelligence analyst do?
Are there any potential downsides of Web 3.0? If so, what are they?
What are the key benefits of threat hunting?
Will machine learning make doctors obsolete?
Could genetics explain the gender gap between men and women in tech?
What are the four foundations of becoming a good data scientist?
What are some key mistakes companies tend to make when it comes to implementing and using big data analytics?
What's the difference between machine learning and data mining?
What are some key things to know about corporate data backup?
How will Web 3.0 change the internet?
How is data analytics being used in the telecom industry?
Why is the idea of technology addiction nothing but a vastly exaggerated problem?
What skills are required get a job in data analytics?
How does a weighted or probabalistic approach help AI to move beyond a purely rules-based or deterministic approach?
How can I secure the devices in my company without degrading the UX?
Why is data visualization useful for machine learning algorithms?
What role will blockchain play in Web 3.0?
Can turning on multifactor authentication boost my security hygiene?
How did Steve Jobs get his first tech job?
What are some of the foundational ways that career pros stand out in machine learning?
What are the security risks associated with endpoint management?
What are some of the dangers of using machine learning impulsively?
Why is endpoint management vital to an effective security strategy?
How is AI technology going to affect the workplace in the near future?
Why are some companies contemplating adding 'human feedback controls' to modern AI systems?
What's the difference between augmented reality and virtual reality?
What does 'connectionism' mean for business AI?
What are some advantages of multi-cloud deployments?
What are some of the potential drawbacks to the gender imbalance in data science?
What are some of the advantages and disadvantages of embedded analytics?
What are some of the resources available to women looking to get into a career in data science?
What is a CX platform and how are companies using the analytics from these platforms?
What components make up an IT infrastructure, and how do they work together?
With more big data solutions moving to the cloud, how will that impact network performance and security?
How can data analytics help smaller companies compete with bigger competitors?
How can data analytics help companies build stronger branding strategies?
What benefit can real-time data provide that data at rest can't?
What does a data management platform do?
What's better, a platform or a bring-your-own machine learning algorithm on AWS?
How are data management and data analytics related?
What are network management services and how does the use of analytics here contribute to better IT management?
What are some of the key ways in which AI can handle data better than humans?
What is the difference between deep learning and machine learning?
What are some common misconceptions about data center infrastructure and how do they impact the business?
What kinds of business problems can machine learning handle?
How can small businesses integrate machine learning into their processes ... or should they even do so?
What is intelligent cloud and what factors are driving its growth?
What are some of the key concerns about the use of big data in health care and how can they be mitigated?
What are some of the key pitfalls of big data contracts and how can companies avoid them?
What should companies consider before starting to use big data as part of their BI strategy?
What are some key ways to automate and optimize data science processes?
What are some of the key challenges of big data when it comes to digital forensics?
What are some of the key privacy concerns around the use of big data?
What are some of the biggest innovations happening in the big data space?
What are some of the key issues to consider in a big data storage strategy?
What are some of they key things that cause big data projects to fail?
What process should a company go through to determine whether big data is a fit for their goals?
What is server sprawl and what can I do about it?
How does software-defined networking differ from virtual networking?
What is the difference between cloud computing and web hosting?
How can cloud computing save money?
Why run ML training on a local machine and then run regular execution on a server?
How are chatbots trained?
How can containerization be a good choice for a machine learning project environment?
How does AI interact with robotics?
Can AI detect your sexual or political orientation by looking at your pics?
Are self-driving cars safer than cars driven by humans?
How is virtual reality going to improve senior care?
How is machine learning used in anti-malware applications?
Is AI going to replace computer programmers anytime soon?
How does artificial intelligence compare to man-computer symbiosis?
Is artificial intelligence a tool or a threat to cybersecurity?
Why is telecom expense management (TEM) important in health care?
Why are some people worried about artificial intelligence?
Can AI help in the battle against fake news?
How is artificial intelligence used in video games?
Could AI provide us with tastier food than human cooks?
Can an AI chatbot really pass for a person?
Why are artificial recurrent neural networks often hard to train?
What is the difference between SCSI and SATA?
What is the 'AI winter' and how did it affect AI research?
What's behind the big 'quantum rush'?
How is data measured?
How can machine learning help to observe biological neurons - and why is this a confusing type of AI?
What are some ethical issues regarding machine learning?
How do the Chrome Store's malicious ad blockers show the duplicity that end users face in cybersecurity?
What is the difference between WEP and WPA?
What are some key ways that the IoT is affecting health care?
Why do security professionals consider bitcoin and cryptocurrency mining a potential for 'parasitic' hacker activity?
How does NeuroEvolution of Augmenting Topologies contribute to genetic machine learning?
Which medical professions can ethically be replaced with AI?
How is AI affecting the military market?
What is the difference between supervised, unsupervised and semi-supervised learning?
How does Saudi Arabia's Sophia robot raise frightening new cybersecurity questions?
Why is data annotation important in some machine learning projects?
How does max pooling help make AlexNet a great technology for image processing?
What is the difference between IPv4 and IPv6?
How can new MIT chips help with neural networks?
How is machine learning affecting genetic testing?
How might machine learning tools evaluating emotion help with call center problems?
Will machine learning advances spur cross-platform data set deployment?
How is artificial intelligence enabling brain boost to enhance memory with electrical brain stimulation?
What are the five schools of machine learning?
Why are machine learning rational agents so important to retail applications?
How is the master algorithm changing the machine learning world?
Why are machine learning experts talking about Xavier initialization?
Why do AI engineers have to worry about intuitive engines?
How can AI revolutionize consumer markets through automated search?
How do chatbots deal with accents?
Why are some experts saying that AI will 'destroy digital authenticity'?
Why are deep learning, machine learning and AI so important in telemedicine and other types of medical services?
What is the difference between speech to text and chatbots?
Why is DARPA researching 'explainable AI'?
How does dynamic allocation in the cloud save companies money?
Why might some machine learning projects require enormous numbers of actors?
How can engineers evaluate training sets and test sets to spot possible overfitting in machine learning?
Why are companies sourcing GPUs for machine learning?
Why should companies be considering intent-based networking?
What does "mobile compatible" mean?
Why might companies invest in "character AI"?
Why is semi-supervised learning a helpful model for machine learning?
What is the difference between a mobile hotspot and tethering?
Why does 'bagging' in machine learning decrease variance?
How can the Chinese restaurant process and other similar machine learning models apply to enterprise AI?
How can a local area network (LAN) be secured?
How can new machine learning capabilities enable the mining of stock documents for financial data?
How do deep stubborn networks play a role in AI evolution?
Why is feature selection so important in machine learning?
How can engineers use gradient boosting to enhance machine learning systems?
How can a 'random walk' be helpful in machine learning algorithms?
What is the difference between a virtual machine and a container?
Why are people talking about the 'tipping point' for machine learning?
Why is TensorFlow so popular for machine learning systems?
What does big data mean for official statistics?
How can a convolutional neural network enhance CRM?
What are some ways that machine learning systems can be helpful for human resources?
How does network scanning work?
How can machine learning work from evident inefficiencies to introduce new efficiencies for business?
Why is consumer ML/AI technology so "disembodied" compared to industrial mechanical/robotics projects?
How has data scraping for machine learning become the most labor-intensive bottleneck since manual data entry in legacy migration?
Why are huge numbers of image files important to many machine learning projects?
How might the concept of equilibrium inform machine learning projects?
How does Amazon Web Services (AWS) facilitate AI opportunities for clients?
Why is bias versus variance important for machine learning?
What is the difference between little endian and big endian data formats?
How does Occam's razor apply to machine learning?
Why is the "information bottleneck" an important theory in deep learning?
What is the difference between a private cloud and a virtualized data center?
How is network mapping different than network monitoring?
How can learning agents "learn to use the web"?
How are companies trying to add a speedometer to artificial intelligence work?
Why is patch management so important in cybersecurity?
Why are companies paying so much for AI professionals?
How do administrators find bandwidth hogs?
How might businesses use the AI potential of real-time data systems like SAP HANA?
What is the difference between a network switch and a network router?
Why is it important to manage a relational database system in the cloud?
How did Moore's law contribute to the current AI revolution?
What is the difference between scale-out versus scale-up (architecture, applications, etc.)?
How can neural networks affect market segmentation?
How can businesses innovate in managing data center bandwidth?
What are some important aspects of file integrity monitoring?
How do admins use server monitoring to evaluate network performance?
Why is multi-factor authentication an important component of cybersecurity?
Why is machine bias a problem in machine learning?
What’s the difference between SEM, SIM and SIEM?
How are logic gates precursors to AI and building blocks for neural networks?
How can machine learning and AI help move companies from a perimeter approach to cybersecurity?
More isn’t always better. How can organizations reduce the noise in their data to achieve targeted, accurate analytics?
Can the same machine learning tools work for both retail and manufacturing businesses?
How can machine learning help with maintenance, repair and overhaul (MRO) processes?
What do network admins accomplish with a bandwidth analyzer or bandwidth monitor?
How might companies use random forest models for predictions?
How is an induction algorithm used in machine learning?
What does "layered security" really mean?
How might companies use Apache Mahout for machine learning?
What are some factors that contribute to AI "drift"?
How is SIEM different from general event log management and monitoring?
Why might a company shut down a chatbot AI project?
Why might companies use Amazon Machine Learning and related tools?
How is bandwidth monitoring different from other types of network monitoring?
Why is scalable machine learning important?
What are some best practices for cloud encryption?
Why do systems benefit from event log monitoring?
Is big data a one-size-fits-all solution?
What's the difference between a CPU and a GPU?
What's the difference between a host name, a domain name and a fully qualified domain name (FDQN)?
How does visibility help with the uncertainty of handing data to a cloud provider?
How can companies maintain application availability standards?
What is the difference between cloud computing and virtualization?
Why do cloud providers seek FEDRamp certification?
What’s the difference between artificial intelligence, machine learning and deep learning?
How might a team make an app "cloud-ready"?
Why does loosely coupled architecture help to scale some types of systems?
How might companies deal with hardware dependencies while moving toward a virtualization model?
Why does virtualization speed up server deployment?
What is the virtualization "backlash" and why is it important?
Why could a "resource hog" make virtualization difficult?
How might a company utilize a virtualization resource summary?
Why do undersized VMs lead to latency and other problems?
What are some of the positives of a demand-driven migration model?
Why should cloud services offer both elasticity and scalability?
What are some of the values of real-time hybrid cloud monitoring?
Why might a company assess right-sizing on-premises versus in the cloud?
How can companies deal with “dynamic unpredictability?”
What performance issues do users face due to wireless interference problems in an enterprise setting?
What kinds of devices can interfere with wireless signals?
How do you mitigate wireless interference sources in an enterprise network?
What are some basic ideas for optimizing hybrid cloud?
Why do some companies choose Azure or AWS over open-source technologies like OpenStack?
What are some advantages and drawbacks of stateless applications?
Why is it important to look at the "full stack" in virtualization?
How does automation help individual system operators?
How can security be both a project and process?
How do companies develop a "data center BMI"?
How can companies tally up cloud costs for multi-cloud or complex cloud systems?
How can IT security be measured?
Why is a good HTML5 interface important for a business project?
How do companies work toward composable infrastructure?
How can you securely delete files?
How can a manager use a workload chart?
What can virtual machine use cases tell companies about systems?
How can companies work to achieve a desired state?
How can companies cultivate a better approach to “object-based” network changes?
Why do naming conventions for virtual machines help with IT organization?
What are some common challenges in decommissioning applications?
Why is reserve capacity important in systems?
What are some values of cloud-native architecture?
Why is it important to match uptime to infrastructure?
What's commonly involved in site reliability engineering?
What are some important considerations for implementing PaaS?
What are some challenges with handling an architecture's storage layers?
What are some of the benefits of software-defined storage?
What are some things that rightsizing virtual environments can do for a business?
What are some benefits of continuous real-time placement of user workloads?
How can stakeholders use the three key operations phases of autonomic hyperconvergent management?
Why would managers suspend VMs when VDI instances are not in use?
Why do companies choose either persistent or non-persistent VDI?
Why would managers differentiate storage for I/O-intensive workloads?
Why would companies assess quality of service for VMs?
What's the utility of a cluster capacity dashboard?
How can companies use raw device mapping?
Why might someone use an N+1 approach for a cluster?
Why do companies consider platform diversity to be important for cloud systems?
What strategies are companies using to mitigate DDoS attacks?
How do companies balance security, cost, scalability and data access for cloud services?
How do engineers use availability zones in cloud and networking admin?
How do companies battle application sprawl?
What are some benefits of self-driving data centers?
What are some concerns companies might have with a "lift and shift" cloud approach?
What is involved in choosing the right EC2 instances for AWS?
What are some benefits of workload abstraction?
What are some challenges of scaling in OpenStack?
How do companies use Kubernetes?
What methods do companies use to improve app performance in cloud models?
How do businesses use virtualization health charts?
What does secured with WEP mean?
How can you securely erase an SSD?
How can passwords be stored securely in a database?
Why is learning assembly language still important?
What are the benefits of cloud-in-a-box deployments?
What are some of the factors that prevent companies from fully adopting the cloud?
Will converged, hyper-converged and super-converged systems lead to the demise of stand-alone servers?
What are some of the benefits of private cloud?
What are the compliance limitations of public cloud?
How do firms collect data "at the edge" of a network?
What makes application performance monitoring important?
What is the difference between convergence, hyperconvergence and superconvergence in cloud computing?
What are some of the business limitations of the public cloud?
What is the difference between deploying containers inside a VM vs directly on bare metal?
What are the benefits of converged infrastructure in cloud computing?
Why should businesses secure an Active Directory?
Why is it important to have change management tools in place for enterprise systems?
How do companies maximize uptime?
How do companies manage database changes?
How is a private cloud platform different from a public cloud platform?
What is tunneling as it applies to a virtual network?
How do containers differ from virtual machines?
What problems do query plan monitoring techniques fix?
Why should managers guard against database redundancy?
How do professionals use visual query building tools?
How do companies create a business-driven data architecture?
What are some core principles of data governance?
What does a SQL compliance manager do?
How did people interact with computers before monitors were commonplace?
What does defragmentation do for SQL systems?
How does predictive alerting work?
How do engineers monitor SQL queries?
What does a central DBMS interface do?
How do companies create a server inventory?
What is the difference between C and C++?
What are the biggest uses of SQL today?
What kind of maintenance is required for an IT infrastructure?
What is the difference between alpha testing and beta testing?
How is IT infrastructure different from network infrastructure?
How is Office 365 different from other versions of Microsoft Office?
What is a virtual local area network (VLAN) and why would I use one?
What is the difference between a composite key, primary key and foreign key?
How is application software different from system software?
What is the difference between security architecture and security design?
How can I secure my Facebook account?
What does secure browsing mean?
How can a hard drive be erased securely?
How does SQL monitoring work as part of general server monitoring?
How does LAN monitoring differ from larger network monitoring?
What is the appeal of NoSQL databases and what pushes companies to move toward implementing them?
What does partitioning mean in regards to a database?
What circumstances led to the rise of the big data ecosystem?
What is the difference between a NoSQL database and a traditional database management system?
How can existing data warehouse environments best scale to meet the needs of big data analytics?
What considerations are most important when deciding which big data solutions to implement?
How can an enterprise achieve analytic agility with big data?
How has big data affected the traditional analytic workflow?
How can mobile phones be recycled?
What does the mobile network state mean?
What is the difference between mobile and wireless?
What is the difference between mobile communication and mobile computing?
What is the difference between mobile data and Wi-Fi?
What is the difference between big data and Hadoop?
How can I learn big data analytics?
What is the difference between big data and data mining?
What are the advantages and disadvantages of Li-Fi technology?
What is the difference between Li-Fi and Wi-Fi?
What is Li-Fi?
What is Cloud Print and how is it used?
What does big data do?
How does mobile computing work?
How can mobile apps help business?
How can I set up cloud storage?
How can cloud computing help small businesses?
How can I learn to use Hadoop to analyze big data?
What is the difference between cloud computing and mobile computing?
How is containerization different from virtualization?
How are a network analyzer and a network scanner different?
What is the difference between DRS and SDRS?
What is the difference between CPU contention and CPU ready queue?
What's the difference between converged and hyper-converged infrastructure?
What is the difference between a managed service provider and a public cloud?
What is the difference between vMotion, VM migration and live migration?
What are the most common network topologies?
How do administrators use a NetFlow collector?
What's the difference between SharePoint monitoring and server monitoring?
What resources are available for Sharepoint monitoring, Exchange monitoring and analysis of other Microsoft products?
What is involved in active directory monitoring?
What is the difference between sFlow and NetFlow?
What role will the internet of things play in the big data ecosystem?
Is Hadoop for everyone?
What's the difference between software-defined networking (SDN) and network virtualization?
Can mobile phones cause cancer?
What is the difference between security and privacy?
Can mobile phones be tracked?
What is the difference between a mobile OS and a computer OS?
How can cloud computing be used at home?
How can I securely erase or wipe an iPad?
What is the difference between privacy, confidentiality and security?

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Techopedia Q&A