“Artificial intelligence would be the ultimate version of Google. The ultimate search engine that would understand everything on the web. It would understand exactly what you wanted, and it would give you the right thing. We’re nowhere near doing that now. However, we can get incrementally closer to that, and that is basically what we work on.” — Larry Page
Artificial Intelligence is all around us, whether you are aware or not AI has a massive effect on our lives as well as businesses. We can certainly expect some astonishing breakthroughs with continued excitement. AI points the advancement in the machines from physical work that they’ve been doing since industrial revolution to planning, strategizing as well as, making decisions.
Commentators are waiting to see whether this advanced technology will bring utopia letting humans spend their lives more meaningfully. There have been predictions about artificial intelligence ranging from optimistic thoughts to sceptical and jaded. Likewise, the Vice President of SAP Leonardo, shares – “In 2019, AI continue to have a bright future and make our work lives easier and allow us to accomplish more. Workers will be able to choose their own task or able to delegate projects to the machines based on preferences.”You can certainly say that it is hard to evade from the AI’s suffusing in media, politics, culture and many more.
AI assistance is in the progression of amounting human speech, Duplex, a Google’s new digital-assistance shows a clear demonstration by scheduling a hair salon appointment or calling a table for two in a restaurant. Also, with the furtherance of generative AI, this technology will induce imagination throughout a global culture, political discussions.
AI’s industrialization has taken hold of the enterprise end-to-end
DevOps is a business-driven approach to deliver software. AI makes up the technology that integrates into the system. AI became the industrialized process in many enterprise solutions. In the yesteryears where a human judgement was required to complete a task, from data preparation to modelling, training and serving – AI tools will automate these tasks. Feature engineering will let accessibility to the capabilities of building, training, clicking and deploying models in a single click through declarative specifications. Not just this, AI workbench will let the users differentiate through industrial grade functions – inline operational experimentation, automated model benchmarking, 24X7 A/B testing, continuous champion-challenges deployment, turbo-powered ensembling, and lifecycle model governance.
TensorFlow, Kubernetes inherit AI for scaling, managing containerized app
Containerized statistical models within cloud-native computing environments are built and deployed for orchestration across Kubernetes clusters. AI’s magic is known to everyone which is being implemented in the fastest runtime engines. We expect that AI versions and its other principal framework will be rolled out in this year in order to accelerate superior cloud-to-edge performance.
TensorFlow, Google’s open source framework is a dominant one. It is expected that within this year TensorFlow will be used to formalize the development and governance of the industry group. Also, it will be useful to the open-source project ecosystem for increasing the convergence with Kubernetes containerization deployment.
AI initiatives work at its best when combined with prime algorithms, trained models, and training data for the application domain. These are capable to provide a potential monetization opportunity – both for redeploying AI assets as well as publishing of equivalent assets.
AI risk -mitigation controls will accelerate along with democratization of BI
AI-infused predictive analytics, search and forecasting tools will remake the business intelligence. Over the past few years, BI has infused AI offering sophisticated solutions in memory interactivity, self-service simplicity and next-best-action prescription with insights of complex data. Thus, the convergence of the traditional focus of technology on historical analytics has changed with the new generation of AI.
Artificial Intelligence brings along a rife of risks, from designing limitations to inadequate runtime governance to the complexity of Blackbox. Commercial AI developmental tools will cross these boundaries incorporating standard workflows and templates to alleviate privacy encroachments, socioeconomic biases, adversarial vulnerabilities, interpretability deficiencies, and other risk factors.
GPU and Blockchain explores the Artificial Intelligence revolution
Artificial intelligence revolution had GPU’s core image processing acceleration competency at its heart. With the adoption of intelligently mixed reality, smart camera, gaming and other apps that rely on real-time, high-fidelity, and immersive image processing. The revolutionary NVIDIA Turing architecture, with all new GeForce RTX platform, together combined for real-time ray tracing, artificial intelligence, and programmable shading to give a whole new experience of gaming.
Blockchain can help track, understand and explain decisions made by AI about whether the financial transactions are fraudulent, and should be blocked or investigated. AI can also manage blockchains more efficiently than humans. If fed with the right training data, it can instantaneously sharpen its skills and become an expert in cracking codes rather than having to take a lifetime.
AI steps increasingly into matters of international politics
The national interests have been put under fences to protect its trade and defence from major world powers. China has emerged, even after restrictions and tariffs, with its efforts to become self-reliant in the field of research and development. Huawei has developed its own processing chips to expunge the abstain of the reliability on the US manufacturers like Intel and NVIDIA. Certainly, there are critics that expose the danger – One, with the increased adoption of AI, authoritarian might be restrained from the rights to privacy or free speech. Two, the collaboration between the academic and industrial organization is expected to slow down affecting the usefulness of the AI.
The rise in employment with the deployment of AIWith the fright of workless future due to the rising machines might lead humans unemployed. But, Gartner, the world’s leading information technology research and advisory company, depicts that more jobs would be created. With the prediction of 1.8 million lost jobs – 2.3 million jobs will be created in the field of education, healthcare, and public sector. A possibility rises of warehouse workers and retail cashier’s replacement wholesale by automated technology. But in the case of doctors and lawyers, AI service providers have made a concrete effort in assisting them with a repetitive task presenting their technology to work alongside human professionals. Although financial services outlook this concept as bit gloomy. Citigroup CEO Vikram Pandit predicted that the human workforce could be reduced by 30% within 5 years and the back-office functions would increasingly be managed by the machines.
To Conclude –
Artificial Intelligence is a prolific platform for new creation in each sector associated with our lives. Its effectual predictions in every possible evolution segments like chatbots, smart cameras, autonomous vehicle, and many more trends are just the beginning of the discussion. Unlike a few years, AI has become pervasive and will continue to accelerate. Also, with the rise in AI concerns over ethics, economics and safety seem to progress with time.