Consultant - Technology Solutions

Providing/Performing  Solution Architecture, Data Architecture, Data Engineering and Technical Optimizations within:

Generative AI, Machine Learning, Artificial intelligence, Python, Azure, AWS, Google Cloud, Oracle Cloud, IBM Cloud, SAP Cloud,  CockRoach DB, YugabyteDB, Oracle, SQL Server, PostgreSQL, Neo4j, GraphDB, Data Science, Data Analytics, Mongo, Cassandra, CouchDB, Hadoop, Kafka, and many other advanced technologies that support Data Pipelines, Data Solutions, Automation and other advanced technological needs.

VP - Solutions Architecture / AI, MI, Gen AI, Data Architecture / Cloud Architecture / Data Science

Data Intelligence, Data Driven Insights, Leadership, Innovation

Set the vision and lead the strategic development and growth of managed IT services organization, inventing, incubating, and scaling ideas for innovation and implementation across North America. Chart a pathway for combining data preparation and storage, data analysis, governance, and consultancy functions while serving as a key inspiring leader in driving all levels of strategy execution by establishing the roadmap and engagement model for data science and analytics utilizing business and industry knowledge. Collaborate with executive peers to drive short-term and long-term transformation and evolution of offerings to continuously meet client needs. 

Key contributions:
•	A key contributor to the formulation of the company's business and digital strategies.
•	Provide insights on emerging technologies and digital trends relevant to enterprise goals and evolving needs.
•	Develop Big Data and IT vision, strategy, and roadmap and determine capital investment parameters, priorities, and risks for enterprise-wide IT initiatives to maximize ROI.
•	Handle all recruiting and hiring of upper and mid-level Information Systems managers, systems engineers and developers.
•	Identify opportunities and develop a business strategy to leverage Artificial Intelligence and Machine Learning ecosystems. 

Hands-on Technical Contributions:
Top Use Cases (cannot provide client names)
•	360-degree customer view; Multi-Data Source and Analytics/Machine Learning data profile;
•	Positive Train Control; Automated Train Control to prevent Life Loss; AI/Machine Learning/Large Data-Driven Datasets;
•	Price Optimization; (B2C) / (B2B) enterprise big data analytics to optimize customer pricing;
•	Operational Efficiency; Using data to identify potential opportunities to streamline operations with data-driven solutions;

VP - Data Driven & Thought Leadership, Cloud & Enterprise Architecture

Lead Big Data SME

Cloud / Big Data / Cloud Migrations
•	Architect - AWS, AWS RDB, AWS Data Warehouse, AWS Redshift & AWS Storage solutions
•	Architect – EC2, S3, CloudFormation, RDS, CloudFront, VPC, Route53, IAM, CloudWatch, Beanstalk, Lambda
•	Architect –Data Migrations from Oracle, SQL Server and Hadoop (Hive / HDFS) to Snowflake Databases
•	Architect – Oracle PaaS, Oracle Infrastructure Cloud, Oracle SaaS Cloud - Data Strategy - On-Prom Oracle to Oracle Cloud
•	Architect – Oracle Cloud Data migration strategy from On-Prem to Oracle Cloud, Spark, Databricks, Snowflake Cloud DB
•	Engineer – SnowFlake Data Warehouse -Data Migration Strategy from On-Prem to SnowFlake DW solution - Ingestion Plan
•	Architect – Data ingestion from 35 data sources via AWS GLUE into AWS RDB, AWS Data Warehouse, AWS Redshift
•	Engineer – Created data ingestion custom Scala, Python, SQL to import custom libraries and Jar files into AWS Glue ETL
•	Engineer - Data Pipeline Design, AWS GLUE to AWS Data lake / AWS Storage – Oracle, DB2, SQL Server, MySQL
•	Architect – Azure Data Factory, Data Pipeline Design, Azure Data lake / Azure Storage – Oracle, DB2, SQL Server, MySQL
•	Engineer – Azure Data Flow, Data Modeling in Azure, and Azure Ad-HOC Reporting (design/development) 
•	Engineer – Google Cloud Platform Data ingestion, Analytics datasets, data lake integration, data migration to Google Cloud
•	Engineer – Google Cloud Platform to Kafka and Spark cluster solutions, Google Cloud Platform to Azure via HDFS/Hive
•	Architect – Google Big Query for use cases where other Hadoop Solutions didn’t provide the results needed by the business.
•	Architect & Administration (Azure) Cosmos DB data migration from Cassandra DB (ALL Seeded Data) 400TB / 35 Sources
•	Engineer - Azure Data Bricks, Azure Data Lake Service, Azure SQL Data Warehouse, Azure Data Catalog
•	Architect & Administrator (Azure) Cosmos DB – Schema Design, Data ingestion, Performance and Query optimization

Sr Director - Cloud & Data Architecture / Big Data Architecture / Data Engineer / Data Science

NoSQL Database Technology

NoSQL Database
•	MongoDB –Full High Availability within two data centers. Document store for more than 5000 users.
•	Neo4J  -Graphical Data – Query, Analyze for highly connected data; Native Graph Storage, Native Graph Processing
•	Neo4J - Graph scalability, high availability, Graph Clustering – Graphs on Spark, Graphs in Azure Cloud Graph Platform
•	HBase - Clusters Design, Management, including backup/recovery, replication, cluster failover, and disaster recovery
•	HBase – Large structured and unstructured Datasets from multiple data sources – a pipeline to Hadoop / KAFKA Clusters
•	GreenPlum – Cluster Management, Cluster Performance Tuning; Query Performance Tuning; Storage Management
•	Greenplum – Maintain Cluster security; Implement Infrastructure Scaling Up/Down; 
•	Greenplum – PFX HDFS, GPMapReduce, Pivotal HD, Spark Connector, Scala, Python (Data Frames), SQL
•	Greenplum - Setup new users and providing access to HAWQ, HDFS, Yarn, Hue using Ranger Kubernetes and Vault;.
•	HBase - Clusters Design, Management, including backup/recovery, replication, cluster failover, and disaster recovery
•	CosmosDB – Migration from AWS Redshift to Azure Snowflake / CosmosDB.  Ingestion of 900B records;
•	Cosmos DB – DB (Schema) Design, Indexing, Change Feed utilization, Azure Functions, and Performance Optimization. 
•	CosmsoDB – Change Feed to Databricks and Data Warehouse for real-time data solutions for different groups of users.
•	Couchbase - 5.0/4.6.x (15 Node/Cluster) Document Data modeling, Cluster Management w/ Hadoop HDF 
•	Couchbase - Node Configuration, Data Conversion to JSON, Hadoop/HDP
•	Cassandra – Capacity planning and requirements gathering for multi-data center Cassandra cluster
•	Cassandra – Installed, Configured, Tuned Datastax Enterprise Cassandra multi-node cluster (4 Data centers and 5 nodes per)
•	Cassandra – DevCenter, CQLsh, OpsCenter, Node tool, UNIX, Cassandra-stress, Shell Scripting, Maven

Certified Database Technology Expert (NoSQL)

Big Data Consultant

Data Governance – Master Data Management
•	Led the creation of Data Governance vision, charter, framework, committees, and processes for the enterprise.
•	Led the implementation, design (one full lifecycle) of Master Data Management (MDM) using MuleSoft / Talend.
•	Proven "hands-on" MDM experience with expertise in MDM strategy proposal, roadmap, and planning 
•	Phased implementation leveraging best practices and a strong focus in data quality
•	Experience in the design/architecture of MDM Hub, data integration, data governance process, and data quality. 
•	Proficient using Talend, Profisee Maestro, Informatica Siperion and IBM Infosphere MDM, DQ & DG tools.
•	Data Hub Repositories – MDM, DQM, Data Library - Maintain Mappings, Match Rules, Purge Party & Merge Party Records

Data Science / Languages
•	R & Python with comprehensive proficiency; Scala – Architecture & Collection Library, REPL, Scala, Refection, Macros
•	Deployment of Hadoop and Spark ecosystems.
•	Machine Learning Frameworks - Amazon Machine Learning / Azure Machine Learning / Singa / H20 / Spark MLLib
•	Machine Learning Frameworks (Streams) - Massive Online Analysis / Spark MLLib 
•	Regression, trees, neural networks, survival analysis, cluster analysis, forecasting, anomaly detection, association rules.
•	Detailed understanding of machine learning pipelines and the ability to discuss concepts such as feature discovery/engineering, model evaluation/validation, online vs. offline learning, and model deployment.
•	Create predictive and clustering models utilizing Oracle, SQL Server, and HDFS data sources
•	Define when predictive or clustering models could be utilized, and the type of data required to make them insightful
•	Enhancing data collection procedures to include information that is relevant for building analytic systems
•	Data mining using state-of-the-art methods and produce actionable insight
•	Design and develop predictive models and machine learning algorithms using advanced methodologies

Lead Data Governance / Lead Data Scientist

Social

Dr. Brown has a true passion for learning, earning six university degrees, including a doctorate in Management Information Systems, a doctorate in Computer Information Systems and a Doctorate in Computer Engineering. Dr. Brown also holds more than 25 technical certifications including Big Data and Data Science. He passes on his expertise through mentor programs that help HS and College students find careers within the technology field.

As a social influencer, Dr. Brown's only mission is to connect innovative emerging technologies with individuals, companies, business leaders and anyone whom will listen. Dr. Brown uses his influence to educate, motivate, substantiate and appreciate the power of DATA and its impact on the global community.

•	Top 100 Big Data Social Influencers
•	Top 100 Data Science Social Influencers
•	Top 100 Digital Transformation Social Influencers                                       
•	Top 100 IoT (Internet of Things) Social Influencers
•	Top 100 Cloud Technology Social Influencers
•	Top 100 Artificial Intelligence & Machine Learning Social Influencers
•	Top 100 Data Intelligence Social Influencers
•	Top 100 FinTech (BlockChain) Social Influencers
•	Top 100 Network (5G) Intelligence & Autonomous Social Influencers

Technology & Business Social Influencer

Data Technology SME

SQL Database
•	Database Refactoring, Database Upgrades, Database Migrations, Database Platform Changes (SQL->SQL, SQL->NoSQL)
•	Database connection pooling and configuration (Oracle, SQL Server, DB2, PostgreSQL)
•	Migration from Informatica ETL / ELT methods into Azure Data Factory Data Pipeline architecture.
•	Data Pipeline from relational database into cloud data lake and data storage using ETL extraction via Azure Data Factory
•	Oracle – Oracle Performance Tuning, backup & recovery, DevOps Automated Changes, Data Migrations, ETL
•	MySQL – (Percona 5.7.x) – 15+ PRD DB’s Percona Cluster; (MariaDB 10.1.x, 10.2.x, 10.3.x) 20+ TST/DEV
•	MySQL – Replication, cluster configurations, sharding – IaaS (On-Prem & Cloud), Index, Elastic Search 
•	PostgreSQL DBA 9.5/9.6 (20+ PRD DB’s. Data Ingestion, Data Model optimization, Table/Index Optimization
•	PostgreSQL DBA – Backup/Recovery, Performance Tuning, Data loads, Connectors to other environments, SQL Tuning
•	PostgreSQL DBA – Replication and Replica Management; Sync Management and Optimization; 
•	PostgreSQL DBA – Query, Storage, Index, - Data Analytics Optimization.
•	Exadata – X5 migration to X7 4 node NVMe 18 Core configuration;
•	Exadata - Migration from Oracle RAC to Oracle Exadata multi-tenant (RAC) Cluster
•	Exadata – Parallelization Optimization, Index Optimization, Partition optimization, Stats optimization
•	Exadata – Perf. tuning, Optimizer optimization, Configuration optimization, Smart Scans optimization
•	Exadata – EXACHK, ASM, ClusterWare, DCLi, CellCLi, - Storage, Operating System and Network 
•	ODI – Oracle 12C Data Integrator configuration with Hadoop/Hive & Oracle DB integration; 
•	SQL Server – SQL Profiler, Indexing Optimization, Parallel Query Optimization, Storage Optimization (Data Files, Logs)
•	Netezza - (15+ PRD DB’s) – 30+ Dev/TST/PRD DB’s (Log Shipping, Replication Server, DB Mirror);
•	Netezza - Provided technical efficiency performance and security functions of Netezza databases.

Certified Database Technology Expert (SQL)

Untapped Potential - The Supreme Partnership of Self

Untapped Potential - The Supreme Partnership of Self written by Craig Brown, PhD (https://twitter.com/supremepartner) was written in December 2015 and will be released in May 2016.  Link for PURCHASE (https://www.createspace.com/6346163).

Author

Dr. Craig Brown is a top Techpreneur and Technology expert covering 30+ years of various technological and innovative projects for top fortune 1000 companies. He is also a Big Data, Data Science and Data Analytics subject matter expert. As a technology & business consultant, in the technology industry, he seeks to offer advice that minimizes the use of technical jargon and maximizes the use of real language, helping ease challenges that most companies and professionals face daily. Brown has doctoral degrees from University of Pennsylvania and Cornell University, an MBA from the Wharton School of Business and BS degrees from University of Pennsylvania. Dr. Brown has earned 25 professional certifications in technology & business and is a leading expert in the IT arena.

Focus: Thought Leadership -Big Data, Database, Cloud, Artificial Intelligence, Machine Learning, Data Science 

Websites
www.craigbrownphd.com -> Personal
https://twitter.com/craigbrownphd -> Twitter
https://www.facebook.com/DrCraigBrown -> Facebook


Google updates Vertex AI with new LLM capabilities, agent builder feature: Google has added new large language models (LLMs) and a new agent builder feature to its AI and machine learning platform Vertex AI at its annual Google Cloud Next conference.

The LLM include a public preview of the Gemini 1.5 Pro model, which has support for 1-million-token context.

The expanded support for context allows native reasoning over enormous amounts of data specific to an input request, the company said, adding that it has received feedback from enterprises that this expanded support can eliminate the need to fine-tune models or employ retrieval augmented generation (RAG) to ground model responses.

To read this article in full, please click here

Craig Brown, PhD

infoworld.com • 4 min read

Google updates Vertex AI with new LLM capabilities, agent builder feature

How to Use Claude in Google Sheets: Introduction Spreadsheets are essential tools for data analysis, but complex formulas can hold you back. That’s where Claude for Sheets, a revolutionary AI add-on from Anthropic, comes in. Ask questions directly in your spreadsheet and get insightful answers using natural language. Claude simplifies complex tasks and opens spreadsheets to a wider range of users, transforming […]


The post How to Use Claude in Google Sheets appeared first on Analytics Vidhya. #DataAnalytics #DataScience #DataDriven #CIO #SaaS #ITManager #ML #DeepLearning

www.analyticsvidhya.com • 3 min read

How to Use Claude in Google Sheets

Knowing when you’re done…: I’ve written before about my inglorious career as an electrician. While I absolutely appreciate the practical and life skills that completing an apprenticeship gave me, it’s fair to say that electrician-ing wasn’t my sweet spot. I simply didn’t enjoy it and I have vivid memories of the downcast feelings I experienced on a Sunday afternoon as I realised I had to go to work the next day.


So it’s no surprise that I spent much of my time during my apprenticeship engaged in anything other than work. Much of this engagement (and, it must be stated, also shared by a couple of my work buddies) involved hanging out at what was an absolute institution in the Wellington cycling scene, Cycle Services. Cycle Services (CS for those in the know) was a small bicycle shop started by a couple of guys who had a deep passion for cycling and the bicycle industry. For nine years before the new millennium, Cycle Services was the hangout spot for the non-mainstream of Wellignton’s cycling community – it was a shop built upon anti-establishment and anti-commercial precepts.


And then in the year 2000 the team at Cycle Services decided their time was done. They’d achieved what they wanted to, it wasn’t getting any easier making a living in the bicycle industry and the sector was increasingly being dominated by faceless corporates with their nationwide chain of large-format retailing. The CS team decided that, since their raison d’etre was a passion for the industry, once that passion was gone they were better to up sticks and move on.


I’ve been thinking about the Cycle Service team this week since I saw the news that New Zealand fashion icon (both individually and from a brand perspective) Kate Sylvester was shutting down. Specifically, I’ve been thinking about the quiet satisfaction that must come from deciding that the time is right to call it quits and call curtains. I don’t have any information about the reason for the Sylvester shutdown, but having been involved in the apparel industry for almost exactly the same amount of time as Kate Sylvester’s 31-year history, I think I can figure it out.


As I’ve opined about so many times before, making stuff is really hard. Making stuff in a sector that essentially doesn’t exist domestically anymore is even harder. Add to that the fact that the current trend is to obsess about the latest tech startup and it’s “zero to a billion in five years” story. More pedestrian business examples just don’t garner as much attention and hence are unlikely to attract the investment, the high-calibre staff, and the attention that validates the principals’ time and effort. And then there is the absolute travesty that is fast fashion – obviously Shien and its container ships full of rubbish just waiting to be deposited in landfill is the poset child, but it started long before Shein… #BigData #DataIntelligence #Cloud #IoT #ML #AI #BigDataAnalytics #CloudComputing

diversity.net.nz • 4 min read

Knowing when you’re done…

##Technology #tech #DataAnalytics #Cloud #DataIntelligence #ArtificialIntelligence #MachineLearning #ML #CloudIntelligence DSC Weekly 5 March 2024: Announcements Top Stories In-Depth


The post DSC Weekly 5 March 2024 appeared first on Data Science Central. #DataScience #BigDataAnalytics #AI

www.datasciencecentral.com • 1 min read

DSC Weekly 5 March 2024 - DataScienceCentral.com

datafloq.com • 3 min read

The Role of Blockchain in Ensuring Data Integrity

Intel, RedHat, and others join hands for Open Platform for Enterprise AI: In a move that could redefine how generative AI can be used by enterprises sans the present ambiguity over its ability to scale and interoperable across business systems, the LF AI & Data Foundation has announced the launch of the Open Platform for Enterprise AI (OPEA) in collaboration with several technology companies.

The objective is to spearhead the development of open, robust, multi-provider, and composable GenAI systems that are flexible, scalable, and enterprise-grade. Technology bigwigs supporting the initiative include Intel, VMWare, Red Hat, SAS, Cloudera, MariaDB Foundation, Anyscale, and Datastax. The LF AI & Data Foundation is inviting and expecting more members to join the bandwagon.

To read this article in full, please click here #MachineLearning #ArtificialIntelligence #DrivenByData #ML #DataInsights #DataScience #SaaS #5G

Intel, RedHat, and others join hands for Open Platform for Enterprise AI

#Technology #AI #ML #Analytics #Data #Cloud How to Use Claude in Google Sheets: Introduction Spreadsheets are essential tools for data analysis, but complex formulas can hold you back. That’s where Claude for Sheets, a revolutionary AI add-on from Anthropic, comes in. Ask questions directly in your spreadsheet and get insightful answers using natural language. Claude simplifies complex tasks and opens spreadsheets to a wider range of users, transforming […]


The post How to Use Claude in Google Sheets appeared first on Analytics Vidhya. #DataAnalytics #DataScience #DataDriven #SaaS #BigData #ArtificialIntelligence #IoT #AI

Quectel Broadens RedCap Offering With Commercial Availability of RG255C-GL RedCap 5G Module: Quectel Wireless Solutions announced the commercial availability of the RG255C-GL 5G RedCap Sub-6 GHz LGA module, delivering comprehensive 5G and 4G coverage across the globe.  #5G #Network #IoT

www.microwavejournal.com • 2 min read

Quectel Broadens RedCap Offering With Commercial Availability of RG255C-GL RedCap 5G Module

#Technology #AI #ML #Analytics #Data #Cloud Cognizant and Microsoft to Revolutionize Healthcare with Generative AI: Cognizant and Microsoft have united to integrate generative AI into healthcare administration. The collaboration aims to enhance efficiency and patient care across America. It promises innovative solutions to streamline processes and improve outcomes across the healthcare industry. Powering Healthcare Administration with Generative AI Cognizant and Microsoft’s partnership focuses on infusing generative AI into healthcare administration. […]


The post Cognizant and Microsoft to Revolutionize Healthcare with Generative AI appeared first on Analytics Vidhya. #DataAnalytics #DataScience #DataDriven #BigData #ITDirector #BigDataAnalytics #ITManager #Blockchain

www.analyticsvidhya.com • 2 min read

Cognizant and Microsoft to Revolutionize Healthcare with Generative AI

#Tech #AI #ML #Analytics #Data #Cloud What is AWS EMR? Here’s Everything you Need to Know: Introduction How do you tackle the challenge of processing and analyzing vast amounts of data efficiently? This question has plagued many businesses and organizations as they navigate the complexities of big data. From log analysis to financial modeling, the need for scalable and flexible solutions has never been greater. Enter AWS EMR, or Amazon Elastic […]


The post What is AWS EMR? Here’s Everything you Need to Know appeared first on Analytics Vidhya. #DataAnalytics #DataScience #DataDriven #IoT #ML #SaaS #CTO #BigDataAnalytics

www.analyticsvidhya.com • 7 min read

What is AWS EMR? Here's Everything you Need to Know

#CraigBrownPhD: Anthropic Challenges OpenAI and Google With New Chatbot: Despite computer shortages, controversies and lawsuits, A.I. continues to improve at a rapid pace. #Technology #Tech #FutureTech

www.nytimes.com • 2 min read

A.I. Start-Up Anthropic Challenges OpenAI and Google With New Chatbot

datafloq.com • 2 min read

Evolving Cybersecurity: Gen AI Threats and AI-Powered Defence

3 secrets to deploying LLMs on cloud platforms: In the past two years, I’ve been involved with generative AI projects using large language models (LLMs) more than traditional systems. I’ve become nostalgic for serverless cloud computing. Their applications range from enhancing conversational AI to providing complex analytical solutions across industries and many functions beyond that. Many enterprises deploy these models on cloud platforms because there is a ready-made ecosystem of public cloud providers and it’s the path of least resistance. However, it’s not cheap.

To read this article in full, please click here #MachineLearning #ArtificialIntelligence #DrivenByData #BigDataAnalytics #SaaS #5G #BusinessStrategy #AI

3 secrets to deploying LLMs on cloud platforms

#CraigBrownPhD: Do You Have Experience Working With Boeing? We Want to Hear From You.: Boeing’s quality control practices have been criticized after a panel on one of the company’s 737 Max jets blew open during a flight in January. #Technology #Tech #FutureTech

www.nytimes.com • Subscription may be required

Do You Have Experience Working With Boeing? We Want to Hear From You.

21st Huawei Analyst Summit: Thrive with Intelligence: The 21st Huawei Analyst Summit (HAS) kicked off today in Shenzhen. #HuaweiUSA #5GGearUp #HWMBBF #AR #DataIntelligence #5GCity #Cloud #MachineLearning

huawei.com • 2 min read

21st Huawei Analyst Summit: Thrive with Intelligence

GitHub’s Autofix Automatically Detects and Fixes Code: In a bid to revolutionize the debugging and vulnerability remediation process, GitHub introduces an innovative AI-powered tool that automates the detection and fixing of code vulnerabilities. This new feature, called Autofix, leverages the synergy between GitHub Copilot and CodeQL. With Autofix, the platform aims to streamline the coding experience while bolstering security measures. Also Read: […]


The post GitHub’s Autofix Automatically Detects and Fixes Code appeared first on Analytics Vidhya. #DataAnalytics #DataScience #DataDriven #BigDataAnalytics #DeepLearning #ITDirector #SaaS #ML

GitHub's Autofix Automatically Detects and Fixes Code

Private Wireless RAN Revenues up ~40 Percent in 2023: According to a newly published forecast report by Dell’Oro Group, Private Wireless Radio Access Network (RAN) revenue growth slowed in the fourth quarter on a year-over-year (Y/Y) basis; however, full-year revenues still accelerated around 40 percent in 2023. #5G #Network #IoT

www.microwavejournal.com • 1 min read

Private Wireless RAN Revenues up ~40 Percent in 2023

#Tech #AI #ML #Analytics #Data #Cloud Cognizant and Microsoft to Revolutionize Healthcare with Generative AI: Cognizant and Microsoft have united to integrate generative AI into healthcare administration. The collaboration aims to enhance efficiency and patient care across America. It promises innovative solutions to streamline processes and improve outcomes across the healthcare industry. Powering Healthcare Administration with Generative AI Cognizant and Microsoft’s partnership focuses on infusing generative AI into healthcare administration. […]


The post Cognizant and Microsoft to Revolutionize Healthcare with Generative AI appeared first on Analytics Vidhya. #DataAnalytics #DataScience #DataDriven #BigData #Blockchain #ArtificialIntelligence #MachineLearning #ML

Apple Wants Google’s Gemini AI to Power iPhones: Apple Inc. is reportedly in discussions with Google regarding the integration of Google’s Gemini AI engine into future iterations of the iPhone. This potential collaboration signifies a strategic move by Apple to bolster its AI capabilities and enhance user experience on its flagship devices. Let’s delve into the possibilities and implications of this partnership. Also […]


The post Apple Wants Google’s Gemini AI to Power iPhones appeared first on Analytics Vidhya. #DataAnalytics #DataScience #DataDriven #AI #CTO #MachineLearning #ITManager #BusinessIntelligence

Apple Wants Google's Gemini AI to Power iPhones

MTN and Huawei launch Joint Technology Innovation Lab to drive Africa's digital transformation and sustainable development: MTN Group, in partnership with Huawei, officially inaugurated the Technology Innovation Lab at MTN Group's headquarters today. #HuaweiUSA #5GGearUp #HWMBBF #ArtificialIntelligence #Cloud #Automation #Mobility #VR

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