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Artificial Intelligence

Open-Sourcing Meta’s Large Language Model Has More Harm Than Good

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Open-Sourcing Meta’s Large Language Model Has More Harm Than Good

Open-source language model of Meta is set to have a harmful impact on the tech market

Mark Zuckerberg is not lagging behind in the artificial intelligence domain and is focused to fully utilizing cutting-edge technologies to the next level. Meta has now announced the launch of the new language model with artificial intelligence known as OPT or Open Pre-Trained Transformer. The open-source language model of Meta is known as a tough competitor of OpenAI GPT-3 artificial intelligence model. It offers the access to a fully-trained large language model. There is a concern regarding the pros and cons side of OPT of Meta that can affect the entire global tech market.

Meta OPT is focused on being a better open-source language model than the GPT artificial intelligence model. It will be able to provide more responsible and reliable research for the community of researchers on a large scale. Meta has decided not to share OPT for any non-commercial use. It has released its language model with pre-trained models, an underlying book of codes, and a logbook of the entire development process.

Meanwhile, Meta is facing some concerns about the artificial intelligence algorithms with harmful impacts on society more than the beneficial side. OPT consists of some of the key shortcomings that can harm the functionalities of the open-source language model. The artificial intelligence language model is known for not working well with declarative instructions and point-blank interrogatives. OPT can generate toxic and abusive language with harmful stereotypes. These are key points that can make the Meta open-source language model have more harmful effects than the benefits part. OPT is known for being repetitive and getting stuck in a loop while understanding human language and behaviour.

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Meta with its open-source language model has been participating in the fast artificial intelligence race to have a clear understanding of the dangerous world of cutting-edge technology. That being said, all hi-tech companies like Meta and Google are focused on having a more and better understanding of human behaviour and languages to have more customer engagement in the future. But is it necessary for different companies to work on the same kind of artificial intelligence? It has been observed that Meta OPT can hold the potential to create a more harmful impact than offering to reap the benefits in the tech market.

 

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AIOps

Top 10 AIOps Platforms That Can Help You Better Handle Data

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Top 10 AIOps Platforms That Can Help You Better Handle Data

Identifying goals is a must before buying a tool, as AIOps needs thorough planning and skilful implementation

AIOps are AI-enabled IT monitoring tools which are primarily designed to predict and analyse unusual events, to prevent unexpected breakdowns of the company’s software infrastructure. Usually, zillions of bytes of information are analysed on a day-to-day basis to estimate the exact requirements of the processes, making it possible to calculate the exact price of an operation. The market is flooded with AIOps tools, which can offer immediate succour to the more urgent IT problems. Experts advise IT, engineers, to weigh on parameters such as charting out specific needs of the organization and identifying AIOps goals, as AIOps needs thorough planning and skilful implementation. Here, we provide you with the top 10 AIOps tools available in the market, for primary reading and comparison.

1. Logic Monitor: The only hybrid infrastructure monitor, a cloud-based solution for detecting the glitches in advance. It is a versatile platform for IT operations, as it hosts all the tools in one place, making the data processing job easy. It is a smart tool that can predict anomalies before damage can occur. It correlates data automatically to find the source and enhanced MTTR (mean time to recovery or mean time to restore).

2. Splunk: It catalogues the events using graphics with a deep indexing tool, apart from gathering log files, reporting for tracking performance, and identifying anomalies. It can anticipate problems and identify their source, all at one dashboard. That means it is an automated machine learning tool which does not demand additional training on part of machine learning engineers.

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3. Moogsoft: IT operations are often overburdened with overlapped functions and applications. Moogsoft comes in handy exactly in such scenarios. It can integrate seamlessly with major performance monitoring tools such as Datadog, AWS Cloudwatch, AppDynamics, etc and declutter the duplicated events. By reducing noise with the help of clustering algorithms and historical records, it helps generate clear reports.

4. IBM Watson Cloud Pak for AIOps: A platform, designed with explainable artificial intelligence, spanning across the IT operations toolchain, for decision-makers to handle incidence response efficiently. With its explainable AI, diagnostics become easy with transparent reasoning. IBM Watson Cloud Pak helps find rare insights, and directly deliver them into the tools the teams are already using.

5. Dynatrace: It is an all-purpose AIOps tool which lets you manage data management tasks through one interface. A cloud-native application, which can be seamlessly integrated across all your cloud applications and automate DevSecOps effortlessly. It is capable of generating real-time alerts and performing synthetic monitoring of online or cloud-based apps, that too at all levels of applications. Identifying problem regions is pretty much easy with its excellent visualisation features.

6. Grok: A highly scalable AIOps platform is capable of providing solutions to the most difficult problems within minutes. It fares much better than many other AIOp platforms in bypassing operational tasks. Grok uses traditional ML, along with the HTM engine which is known for its capability in detecting context-specific anomalies, even in the signals which lie beyond the threshold level.

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7. Netreo: With Netreo it is pretty easy to observe the activity across the apps and the root cause analysis helps in zeroing in on the problem, immediately. It effectively sets up the RCA through its insight visualisation, alert features and device activity logs, which in turn cut down incident tickets whenever the device is down. It can analyse a vast amount of data gathered over years to provide near-accurate decisions.

8. Instana: It is a fully automated full-stack AIops with context-based observability to help decision-makers take accurate decisions and enhance application performance. It is known for its performance in areas like automated profiling, service, app monitoring, etc. It is an easy to install tool, taking just one file to be configured and comes with a simple, and interesting user interface

9. New Relic One: A leading observability tool which has amazing features like multiple cloud support, simple installation process, GUI, documentation, etc. Its service map lets users keep track of the server-to-server communication easily. Monitor events, logs, traces, and metrics in one secure cloud, and debug directly from the IDE.

10. Pager Duty: Pager Duty is an AIOps tool known for higher uptime, very much required to have better operations. It monitors, analyses, and provides automated incident alerts delivered as e-mails, SMSs, and voice messages as back-ups enabled by its smart operational analytics. Its auditing powers include letting the users know who did what and when.

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Artificial Intelligence

Today, IBM Is The Most Open And Trusted AI For Businesses! Here’s Why

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Today, IBM Is The Most Open And Trusted AI For Businesses! Here’s Why

IBM has transformed itself through acquisitions, breakthrough technologies, and AI innovations

IBM also known as International Business Machines is a global information technology and innovation leader providing computer hardware, software, and infrastructure and hosting services. Headquartered in Armonk, NY, the company is distinguished as being first and foremost company, serving the world’s leaders in their industries. IBM is uniquely positioned in bringing innovative technology and industry expertise on a foundation of trust and security as an integrated proposition to its clients. This integrated proposition permits the company to deliver business impact that matters to its clients, impact that requires bringing together technologies such as hybrid cloud, data and AI insight with workflow and advanced industry skills.

IBM has transformed itself through acquisitions, breakthrough technologies and social innovations. In the year 2019, the company generated US$77.1 billion in revenue, operating gross profit margins of 48% and operating earnings per share of US$12.81. IBM had strong cash generation with net cash from operating activities of US$14.8 billion and free cash flow of US$11.9 billion. The company returned US$7.1 billion in capital to its shareholders, including dividends of US$5.7 billion.

To gain momentum in its digital transformational technologies, IBM has announced that the company will be splitting into two units. According to the company CEO Arvind Krishna, one unit will focus on managing clients’ IT infrastructure, while the other more focused unit of IBM will be devoted to developing cloud computing and AI. The financial details pertaining to the split have not been disclosed by the company, but IBM’s acquisition of Red Hat last year is the driving force behind the company’s split.

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IBM combines the portfolio, people, and sense of purpose necessary to meet today’s enterprise demands. Over the last decade, the company has forged the foundations of its end-to-end, integrated value proposition through a series of transformative actions.

Strategic Capital Investments to Drive Innovation

IBM is known to be flamboyant while investing in technology. Ever since its inception, the company has extensively invested to make the technology more perceptible and accessible for everyone. In an effort to stimulate technological innovations, the company’s major investment areas are cognitive solutions, Global Business Services, technology services and cloud platforms, and global financing. Each year the investment in IBM’s research and development contributes six to seven percent of the company’s total investment.

Since 2012, IBM has devoted significant capital to developing new capabilities. The company invested over US$120 billion to transform its strategy, portfolio, and workforce. Simultaneously, the tech giant returned US$97 billion to shareholders. IBM also invested nearly US$30 billion in capital expenditures, building its cloud and cognitive offerings and strengthening its security and services capabilities. To bolster its research and development, the company has invested US$45 billion in R&D, forging the futures of cloud, AI, blockchain, and quantum computing. In 2019, its inventors received 9,262 U.S. patents, the most ever awarded to a U.S. company. It was its 27th straight year of patent leadership for the company.

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IBM invested US$200 million in the new global headquarters for the Internet of Things (IoT), business in Munich, with new IoT capabilities around blockchain and security. In 2016, IBM heavily invested US$6 billion in Research and Development, nearly US$ 4 billion in capital expenditure and in repurchasing its common stock worth US$3.5 billion. 

The company has also invested US$200 million in building new global security headquarters in Cambridge Massecheuts, which features the industry’s first Cyber Range for the commercial sector. It allows the customers to prepare for and respond to cyberattacks using live malware and real-world scenarios. The company also invested in its global network IBM X-Force Command centres that handle over 1 trillion security events per month and uses cognitive technologies like Watson for client services including chat sessions and data delivery.

For the year 2017, IBM’s investment in R&D accounted to be US$5.6 billion. The company extensively invested in its cloud and AI services, with an investment of US$3.3 billion in net capital expenditures. In 2018, IBM invested US$5.4 billion in research and development. The company also became the highest patent earner amongst the technology giants. Reports suggest that IBM is also investing to rectify the dearth of AI skill shortage by launching a STEM initiative for girls. This initiative will teach 80,000 girls across India about coding and building AI models and has the aim of reaching 2,00,000 students by 2022.

The company has invested US$25 million, in Code and Response, a four-year deployment initiative to put open source technology as part of coding challenges such as Call For Code, in the areas where it is most needed. The initiative includes resources to build, fortify, test, and implement solutions on a large scale. In partnership with Clinton Global Initiative University, this project is first piloted in Puerto Rico, North Carolina, Osaka and Kerala.

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For 2019, the company has invested US$120 billion to transform the company’s strategy, portfolio, and workplace Management. A total amount of US$30 billion was expanded in capital expenditures, thus bolstering the company’s cloud, security, and services capabilities. Moreover, IBM invested US$ 45 billion in research and development, thus accelerating the future of Cloud, AI, Blockchain, and quantum computing. Over the past few years, the company has invested in building 57 studios and 17000 IBM iX digital consultants for assisting the company’s clients.

Till June 2020, the company’s investment in research and development accounted to be US$1.582 billion.

Strengthening Businesses with Product Breakthroughs

IBM has been focused on developing innovative tools and technologies for businesses over the years. The company’s investments have reshaped it to lead in the emerging, high-value segments of the IT market, including analytics, artificial intelligence, cloud, security, blockchain, and quantum computing. Since IBM’s investments are more focused on R&D-backed breakthrough innovations, it has created the company’s strongest portfolio ever and has driven effective outcomes.

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IBM Cloud: Cloud computing is one of the most product segments representing 27%, a US$21.2 billion business, of IBM’s revenue. In the past year, the company has substantially improved its public cloud offerings through IBM Cloud, including significant improvements in ease of use, 99.99% availability, and the strongest security posture in the industry. IBM Cloud has grown too diverse business areas offering enterprises public, private, and hybrid cloud solutions. In 2019, IBM introduced the world’s first financial services-ready public cloud, secure and purpose-built for the industry.

IBM Watson: IBM is the world’s enterprise leader in AI offering IBM Watson to assist companies to produce better decision-making and business outcomes through over 30,000 client engagements, deployed in customer service, healthcare, supply chain, weather forecasts, energy exploration, and other fields. Today, IBM Watson is the most open and trusted AI for businesses, available to run in any environment – on-premise, and in private and public clouds.

IBM Blockchain: IBM improves trust and transparency across business networks through IBM Blockchain by creating a new way for clients to share and secure data. The product powers over 500 client projects, with more than 85 active networks transforming supply chains, global shipping, and cross-border finance. IBM Food Trust, TradeLens, and other initiatives streamline supply chain processes, bringing trust and transparency to transactions.

IBM Security: It was built for industry-leading compliance, threat monitoring and container security. IBM Security has 8,000 subject matter experts serving more than 17,000 clients across 130+ countries. The industry’s leading AI and cloud-based security solutions include IBM Security Connect, launched in 2018, which allows clients to glean, integrate and assess security data across multiple applications and tools, in a vendor-agnostic way.

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IBM Systems produces innovative infrastructure for AI and hybrid cloud. The z14 is one of IBM’s most successful mainframe programs in history, with broad global adoption across 27 different industry segments. In addition, the U.S. Department of Energy’s POWER9-based supercomputers, Summit and Sierra, was ranked the most powerful supercomputers in the world in 2018.

IBM Services was a key driver of IBM’s performance in 2018. Forty-seven engagements worth over US$100 million each helped major clients, including Bank of the Philippine Islands, Juniper Networks, Nordea, Westpac, and Aditya Birla Retail, to move to the next stage of their digital transformations. Through IBM Services, the company helps its clients around the world to deploy AI to their core business processes and workflows, infusing their businesses with automation, intelligence, and continuous learning to transform everything from supply chains and HR to finance and operations.

Quantum Computing: For decades, IBM has led the R&D of quantum information science and quantum machines. The company was the first to give the world the chance to experience it by putting a quantum computer on the cloud in 2016. Today, quantum computing is moving out of the lab and into the hands of users and commercial clients worldwide.

In 2018, IBM also launched a new service called IBM Talent and Transformation, addressing the often-overlooked cultural aspects of AI. This service helps its clients ensure their teams have the right skills and talent, with the supporting culture and work environment, to support a new way of working that is critical to scaling AI for business.

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Expanding Business Horizons Through M&A

IBM is the pioneer of a lucrative business through acquisition and mergers. The company has made 185 acquisitions since 2001, at a total cost of US$87.2 billion. From extending its services in advanced weather forecast to assisting clients with risk management in utilities, IBM’s strategy to spread its operation is applauded by the experts.

In 2016, IBM acquired The Weather Company, the world’s most widely recognized weather media company for US$2 billion. With The Weather Company, the IBM research has made a global forecasting model known as Deep Thunder, which trains the ML model to help businesses predict the actual impact of weather.

In the same year, IBM acquired Truven Health Analytics, which added substantial new capabilities to the Solutions Software portfolio, at a value of US$2.6 billion, and integrated its technology and data for boosting the Watson Health business unit. The company also acquired cybersecurity company Resilient systems, thus boosting IBM’s cybersecurity business, and Optevia, a cloud software integrator, and Bluewolf Group, a cloud software consulting company, playing in leagues with AWS and Microsoft Azure.

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Other acquisitions made by IBM in 2016 include Ustream Inc, AT&T application and hosting services, G4S’s cash solutions business, Sanovi Technologies Private Limited, Resource/Ammirati, ecx International AG, Aperto AG, Bluewolf Group LLC, Fluid’s Inc’s Expert Personal Shopper (XPS), Resilient Systems Inc, EZ Legacy Ltd, and Promonotory Financial Group LLC. The total investment for all the acquisitions in 2016 was US$5.9 billion. 

For the year 2017, IBM made the following acquisitions namely Agile 3 solutions LLC, Cloudigo Ltd, XCC web content/Custom Apps, and Viviant Digital, with an investment of US$134 million. Of which the acquisition of Cloudigo, an Israeli data centre start-up created the buzz. With no financial disclosure of the acquisition, Cloudigo’s data centre infrastructure is integrated with IBM Watson, for advanced network processing. Moreover, the team is building the Cloud Innovation Lab, which is part of the IBM Cloud Infrastructure Group.

In 2018, two companies Armanta Incorporated and Oniqua Holdings Pty Ltd were acquired by IBM for US$49 million. Armanta Inc. is a developer of analytics software for financial firms that is integrated with IBM’s Watson Financial Services Portfolio, whereas Oniqua Holdings Pty Ltd, a maintenance Repair and Operations inventory Optimizations solutions and services company will be integrated with IBM’s IoT capabilities to assist mining, oil & gas, transportation utilities, manufacturing and other asset-intensive businesses with critical insights and risk management.

Apart from this, IBM continues its investments in furthering its portfolio. In 2019, the company acquired Red Hat, the world’s leading open source technology provider for enterprises, for US$34 billion. The acquisition positions IBM as the leading hybrid cloud provider and expedites its high-value business model, extending Red Hat’s open source innovation to a broader range of clients.

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The Future Outlook

The Future Outlook

IBM will continue to enhance its position as the world’s leader in cloud platforms and cognitive solutions through breakthrough innovations. The company will help its clients to unlock the full business value of the cloud. Today, AI and other advanced technologies are substantially changing the very nature of work. Hence, to keep up with the rate and pace of these changes, IBM will further invigorate its workforce skills.

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Artificial Intelligence

Watch Out For How Google Is Adopting AI Being One Of The Top AI Companies!

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Watch Out For How Google Is Adopting AI Being One Of The Top AI Companies!

Take a look at how Google is adopting AI and making investments and acquisitions based on AI

Google, as a brand, is not a conventional company. It performs on the vision of organising the world’s information and making it accessible to users. The vision doesn’t end here, it seeks to evolve with changing times to pace up with new generations of people, technology, and lifestyles.

The company segments its products and services as per demographics, geography, and psychographics to cater to the ever-accelerating demands of the technology market. The company positions itself on the basis of a value-based strategy to make life easier.

Google is the most successful technology company of all time and has an optimal reputation for corporate affairs and responsibilities. Despite being an achiever, the company aims to intensify its core while heightening its market position above all. Google’s market offering comprises a variety of tools and products including search tools, advertising services, communication and publishing tools, security tools, map-related products, and statistical tools to name a few.

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Acquisitions & Mergers Escalate Market Reach

To amplify its market reach, the company is critically focusing on mergers and acquisitions across verticals to support and strengthen its services portfolio. Google has acquired 225 organisations since 1998. The company’s most recent acquisition was at US$163 million for Pointy, a startup based in Dublin, Ireland on January 22, 2020. Pointy provides hardware and software technology to help brick-and-mortar retailers.

In June 2019, Google at US$2.6 billion acquired Looker in an all cash-deal to set up a new competitive front while adding business intelligence to its data analytics tools. Earlier this year in February, the company acquired Israel-based platform Alooma to simplify cloud migration and enhance big data assets in the firm. Google also acquired Fitbit for US$2.1 billion in 2019 to bolster its wearable market.

Google acquired at least 8 robotics companies, including Boston Dynamics, known to make Pentagon-funded advanced robots. Before this, last year in October Google had set its eyes on US-based AI customer service startup, Onward. The acquisition came just a few months after the release of Google’s Contact Centre AI which is an ML-fuelled virtual customer representative that interacts with the caller over the phone. Additionally, back in 2017, Google made its first purchase in India with Bengaluru-based AI-startup Halli Labs which promises to satisfy AI-dreams of the former while applying machine learning and natural language processing technology to strengthen Google’s ambitious strategies. In the same year in March, Google bought Kaggle to merge its cloud platform services with the latter’s data science community reach including data scientists, data engineers, and other data-driven aspiring professionals.

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Also, in September 2016, Google made a move into natural language processing technology via API.AI acquisition enabling developers to build conversational bots for better and enhanced customer service.

Clustering all the acquisitions of the company in recent times, Google is revitalizing its capabilities and technology market reach while offering artificial intelligence, machine learning, cloud migration, big data, and natural language processing empowered services. With the adoption of ML and NLP, the company is at the forefront of revolutionizing customer engagements and their enriched experience.

Magnifying Services Through Strategic Partnerships

Looking at the bedrock of Google’s strategic partnership over the years, we can observe that it is not only enhancing its existing services but also penetrating the cocoon of next-gen technologies and products. Google in its sixth edition of Google For India, conducted virtually, announced its partnership with Prasar Bharati to launch a new initiative to empower small businesses by adopting digital tools to adapt to the current situation due to the COVID-19 pandemic.

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Google partnered with Walmart in April 2019, to enable voice-driven grocery shopping. Also in May 2017, Google allied with automotive aces Volvo and Audi to bring the Android operating system beyond smartphones and directly into futuristic smart cars. Apart from Android OS, the company is willing to impart a great infotainment system to the next stage of autonomous cars through YouTube, while partnering with another automotive giant Tesla.

The same year in November, Google announced its massive strategic partnership with American cloud-based software company, Salesforce. As a part of the deal, Google is employing the latter as its elected CRM (Customer Relationship Management) provider for trading its cloud services.

Google is determined for its new and expanded partnerships with resourceful businesses and is optimistic about its expansion into new global markets. This makes it obvious that the tech giant has the resources and partnered environment to supply demanded services to customers using new-age technologies.

Additionally, Google is modeling key strategic partnerships with Confluent, DataStax, Elastic, InfluxData, Neo4j, and Redis Labs which would offer full-fledged services running in the cloud while optimizing performance and latency between service and applications.

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As the beneficiary of these partnerships, customers will avail of the integrated user interface for app management with the ability to deliver and manage services from Google Cloud Console. Last year, with Confluent, Google declared that the collaboration would introduce Confluent Cloud based on Apache Kafka.

Financial Landscape and Investments

Being a gigantic corporation like this, it becomes mandatory to manage the finances when pacing up with the technological shifts and disruption. Google and Alphabet CEO Sundar Pichai this year on July 13 announced nearly US$10 billion (INR 75,000 crore) to help boost India’s digital economy. It plans to make this investment over the next seven years through a mix of equity investment, partnerships, and infrastructure and ecosystem investments.

As reported two years ago, Google was the most active corporate investor in 2017. The data depicts that, the vital investment arms of Google – Google Ventures, CapitalG, and Gradient Ventures along with Google itself invested in around 103 deals that year. Out of the major investments of Google and its parent company Alphabet, most of them were startups based in various regions. Other than the key equity investments, Google operates Launchpad Accelerator which sanctions US$50,000 equity-free to start-ups based in Africa, Asia, South America, and Eastern Europe.

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Google has made some significant investments in the newest technology-based companies including Agolo, Thrive Savings, Watt Time, Hello Team Solar, KaiOS Technologies, Quill, lowRISC, Iridescent, Actua, Wadhwani AI, and others. The further investments this year will focus on opportunities beyond Silicon Valley and give Google outposts in 24 states.

Offloading to Add Value to Operations

Besides all the investments, acquisitions, and partnerships, it is quintessential for a company like Google to offload some of its assets to create value for the firm and not be distracted from its core business operations.

When it comes to divestitures, the Google-Motorola case is considered a lesson in strategic divestitures of Google’s history. The tech giant bought smartphone manufacturer Motorola for US$12.5 billion in 2011 and around 3 years later, it sold the latter to Lenovo for US$3 billion and presented it as a successful deal. By this divestiture, Google served the objective to assist in supercharging the Android ecosystem by designing patent portfolio for Google and significant smartphones for users. Also, Google had evolved Motorola in the process and the latter released two highly rated budget smartphones – Moto X and Moto G – during its time at Google. Consequently, Motorola became an alluring acquisition target spreading the use of Android and adding a key value driver for Google.

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Ever-Evolving Phenomenon of Research & Development

Away from the plethora of financial aspects, Research and Development are one of the most cardinal parts of Google’s business operations which seek knowledge to develop, design, and enhance its products, services, technologies, solutions, and tools. Balanced investment in R&D not only connects various parts of the company strategy but also accelerated Google’s marketing and business prosperity. Google AI, Google Auto ML Vision, Google Assistant, TensorFlow, and DeepMind are the major R&D hands of the company dealing in artificial intelligence, machine learning, natural language processing, deep learning/AGI accelerators, and artificial general intelligence respectively.

For the past few years, Google is supporting and sponsoring new technologies as a part of its research work. The recent research priorities of Google cover responsible AI practices and evaluation of its own AI development, AI for Social Good, Assistive Technologies like Google Duplex, quantum computing framework including Cirq, development of BERT while focusing on natural language understanding, and Computational Photography (Night Sight). Moreover, Google is focusing on new research including techniques to assist advertisers to experiment with incentive compatibility of ad auctions, and optimizing ad refresh for in-app advertising. The company has also continued its research on its development of open source frameworks for safety and privacy in AI systems like CleverHans and TensorFlow Privacy.

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Strategic Future Prospects

Google is not alone in the race and has a long queue of competitors including Amazon, Microsoft, and many others, to compete with. Although acquisitions, partnerships, investments, and divestitures could lead to operating difficulties, dilution, and other adverse consequences badly influencing business and results of operations but it is quite clear with the above observations that Google is adopting strategic approaches of monetary investments while investing substantially in disruptive technologies empower its operations and functionalities. The use of capital plays an important role in the overall corporate strategy of an organization; therefore, Google is likely to continue to evaluate and enter into discussions regarding a wide array of potential strategic transactions overcoming all financial and corporate risks and difficulties of the current market trends.

Google is likely to build a robot army to make self-driving cars interact with each other while driving, predicting routes, avoiding collisions, and managing traffic on their own. The company aims to go back to space; therefore, it has leased a NASA airfield for US$1.16 billion for 60 years to upgrade its facilities.

Another expected development by Google in the next year could be the up-gradation of Google’s smart contact lens to monitor sugar levels.

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