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Pure Storage Announces Industry-First Generative AI Copilot for Storage

Pure Storage has announced new capabilities in its platform, including the industry’s first generative AI copilot for storage.

This leverages data insights from tens of thousands of Pure Storage customers to guide storage teams through every step of investigating complex performance and management issues and staying ahead of security incidents.

At its flagship event, Pure Accelerate 2024, held in Las Vegas, Pure Storage also Pure Fusion, which unifies arrays and optimises storage pools on the fly across structured and unstructured data, on-premises, and in the cloud.

Now fully embedded into the Purity operating environment designed to continually get better over time via non-disruptive upgrades, the next generation Pure Fusion will be available across the entire Pure Storage platform to all global customers.

“Pure is redefining enterprise storage with a single, unified data storage platform that can address virtually all enterprise storage needs including the most pressing challenges and opportunities IT leaders face today, like AI and cyber resilience. The Pure Storage platform delivers unparalleled consistency, resilience, and SLA-guaranteed data storage services, reducing costs and uncertainty in an increasingly complex business landscape.” – Charles Giancarlo, chairman and CEO, Pure Storage, said.

Also announced at Pure//Accelerate were new capabilities that advance Pure Storage’s existing cyber resiliency offerings, which include SafeMode for ransomware recovery:

Enhanced Cyber Recovery and Resilience SLA: Building on the first-of-its-kind ransomware recovery SLA, Evergreen//One is expanding its coverage to include disaster recovery scenarios as well. This new and improved Cyber Recovery and Resilience SLA delivers a customized recovery plan, ships clean service infrastructure within a defined SLA, provides onsite installation, and supplies additional professional services for data transfer.
In addition, Pure Storage will collaborate with organizations to build and maintain a comprehensive cybersecurity strategy. Ongoing quarterly reviews are included to ensure best practices adherence, ongoing risk assessments, and operational security remediation. Organizations can rest assured knowing if an unforeseen disruptive event occurs, Pure Storage will help rapidly restore normal operations, guaranteed.
New Security Assessment: The new assessment provides deep visibility into fleet-level security risks and offers actionable recommendations to maximize cyber resilience. Based on aggregated intelligence across 10,000+ environments, the Security Assessment presents numerical scores from 0 to 5 to benchmark the security posture of the entire storage fleet.
It also delivers best practices to align with NIST 2.0 standards, advance regulatory compliance, remediate potential security anomalies, and rapidly restore operations if a security-related event occurs. Additionally, the new AI co-pilot leverages the security assessment to provide Chief Information Security Officers (CISOs) with the visibility into benchmarking their security posture against other Pure Storage customers.
New AI-Powered Anomaly Detection Enhancement: Discover threats such as ransomware attacks, unusual activity, malicious behavior, and Denial of Service attacks via performance anomalies. This expands on previously available ransomware detection based on data reduction anomalies. The expanded detection is built on multiple machine learning models running to identify unusual anomalous behavior.
The models analyze customer environments with historical data for anomalous patterns based on heuristics of performance as well as user context on how storage is used. Leveraging this capability, customers can identify the last known good snapshot copy to mitigate operational impact by quickly identifying recovery point targets to restore data, reducing risk and guesswork.

Pure Storage was among the first enterprise storage vendors to work with NVIDIA to achieve NVIDIA DGX BasePOD certification and NVIDIA OVX validation. Building upon this pioneering collaboration for AI-ready infrastructure, Pure expects to be a certified storage solution for NVIDIA DGX SuperPOD by the end of 2024.

Dell is Building AI Factory with NVIDIA GPUs for Running Elon Musk’s Grok

Michael Dell, the CEO and chairman of Dell technologies posted on X that the company is building Dell AI Factory with NVIDIA GPUs for powering Grok, the AI model built by Elon Musk’s xAI.

We’re building a Dell AI factory with @nvidia to power @grok for @xai @elonmusk pic.twitter.com/2aTYLtCBup

— Michael Dell (@MichaelDell) June 19, 2024

xAI does not lack computational resources. Earlier in 2023, Musk acquired tens of thousands of GPUs. Earlier this year, Musk revealed that training the Grok 2 model required approximately 20,000 Nvidia H100 GPUs. He added that the Grok 3 model and future models would need about 100,000 Nvidia H100 chips.

According to another report, Musk aims to have the proposed supercomputer operational by fall 2025. It was also mentioned that xAI might collaborate with Oracle to build this extensive computer system.

Once completed, the interconnected array of NVIDIA H100 GPUs would be at least four times larger than the largest existing GPU clusters, as Musk indicated during a presentation to investors in May.

In April this year, xAI introduced Grok-1.5V, a first-generation multimodal model. In addition to its strong text capabilities, Grok can process a wide variety of visual information, including documents, diagrams, charts, screenshots, and photographs.

“It seems like Elon Musk is assembling an avengers-like team of tech giants and turning them into a formidable force in AI, with Grok as their secret weapon,” said a user on X.
Recently, in a “staggering” revelation, Meta AI chief Yann LeCun confirmed that Meta has obtained $30 billion worth of NVIDIA GPUs to train their AI models. Enough to run a small nation or even put a man on the moon in 1969.

How to Implement Agentic RAG Using LangChain: Part 1

Imagine trying to bake a cake without a recipe. You might remember bits and pieces, but chances are you'll miss something crucial. This is similar to how traditional Large Language Models (LLMs) function, they're brilliant but sometimes lack specific, up-to-date information.

The Naive RAG paradigm represents the earliest methodology, which gained prominence shortly after ChatGPT became widely adopted. This approach follows a traditional process that includes indexing, retrieval, and generation, often referred to as a "Retrieve-Read" framework.

The image below illustrates a Naive RAG pipeline:

This image shows the Naive RAG pipeline from query to the retrieval and the response | Image by author

Implementing Agentic RAG using LangChain takes this a step further. Unlike the naive RAG approach, Agentic RAG introduces the concept of an 'agent' that can actively interact with the retrieval system to improve the quality of the generated output.

To begin, let's first define what Agentic RAG is.

What is Agentic RAG?

Agentic RAG (Agent-Based Retrieval-Augmented Generation) is an innovative approach to answering questions across multiple documents. Unlike traditional methods that rely solely on large language models, Agentic RAG utilizes intelligent agents that can plan, reason, and learn over time.

These agents are responsible for comparing documents, summarizing specific documents, and evaluating summaries. This provides a more flexible and dynamic framework for question answering, as the agents collaborate to accomplish complex tasks.

The key components of Agentic RAG are:

Document Agents: Responsible for question answering and summarization within their designated documents.
Meta-Agent: The top-level agent that oversees the document agents and coordinates their efforts.

This hierarchical structure allows Agentic RAG to leverage the strengths of both individual document agents and the meta-agent, resulting in enhanced capabilities in tasks requiring strategic planning and nuanced decision-making.

This image illustrates the different layers of agents from the top-level agent down to the subordinate document agents | source: LlamaIndex

Benefits of Using Agentic RAG

Using an agent-based implementation in Retrieval-Augmented Generation (RAG) offers several benefits which include task specialization, parallel processing, scalability, flexibility, and fault tolerance. This is explained in detail below:

Task specialization: Agent-based RAG allows for task specialization among different agents. Each agent can focus on a specific aspect of the task, such as document retrieval, summarization, or question answering. This specialization enhances efficiency and accuracy by ensuring that each agent is well-suited to its designated role.
Parallel processing: Agents in an agent-based RAG system can work in parallel, processing different aspects of the task simultaneously. This parallel processing capability leads to faster response times and improved overall performance, especially when dealing with large datasets or complex tasks.
Scalability: The architectures of Agent-based RAG are inherently scalable. New agents can be added to the system as needed, allowing it to handle increasing workloads or accommodate additional functionalities without significant changes to the overall architecture. This scalability ensures that the system can grow and adapt to changing requirements over time.
Flexibility: These systems offer flexibility in task allocation and resource management. Agents can be dynamically assigned to tasks based on workload, priority, or specific requirements, allowing for efficient resource utilization and adaptability to varying workloads or user demands.
Fault tolerance: Agent-based RAG architectures are inherently fault-tolerant. If one agent fails or becomes unavailable, other agents can continue to perform their tasks independently, reducing the risk of system downtime or data loss. This fault tolerance improves the reliability and robustness of the system, ensuring uninterrupted service even in the face of failures or disruptions.

Now that we have learned what it is, in the next part, we will implement agentic RAG.

Shittu Olumide is a software engineer and technical writer passionate about leveraging cutting-edge technologies to craft compelling narratives, with a keen eye for detail and a knack for simplifying complex concepts. You can also find Shittu on Twitter.

Is the UPSC Exam a Reason for Youth Unemployment?

In India, the craze for the UPSC exams is at an all-time high, with many graduates seeing exam preparation as the easiest alternative to job hunting.

“80% of unemployed people are the ones who are preparing for government exams”, said Saloni Khanna, a UPSC interviewer and founder of Skill Up Foundation, on the Raj Shamani Podcast.

UPSC aspirants often share that it takes about 7 months to prepare for the exams, though some may spend years trying to crack it.

Enter PadhAI, an AI app that can reportedly score over 170 out of 200 marks in the 2024 UPSC preliminary exams within just 7 minutes. Additionally, PAiGPT, an AI-powered conversational chatbot for UPSC aspirants, has recently released its app for Android and iOS.

In light of these advancements, dedicating months to prepare for an exam might soon seem outdated.

Education System Needs a Revamp

Recently, a Computer Science graduate voiced his frustration on Reddit. “I’m about to graduate with a CS degree and have never used a “library”, “framework”, or “API”, and am not really sure what they are.” This sentiment highlights the stark reality of how the youth remains unprepared.

According to the India Employment Report 2024, 83% of unemployed Indians are youth. Despite a surge in higher education enrollments, the quality of education remains a significant concern.

Critics argue that outdated curricula in Indian colleges fail to meet industry requirements, creating a big gap between what students learn and the skills they need for the job market.

Back in 2015, esteemed scientist and Bharat Ratna awardee CNR Rao stated that 90% of Indian universities have outdated curricula, contributing to the country’s absence from the top 100 global universities list.

As per the report by the World Population Review, India ranked 34th globally in the quality of education system.

Further, these factors may be driving Indian students to pursue higher education abroad. According to Bureau of Immigration statistics, only 40,431 foreign students came to India for higher studies in 2023, while 7,65,000 Indian students went abroad for studies.

Redefining the Indian Education System

Adobe CEO Shantanu Narayen highlighted a trend: many young Indian professionals are choosing to stay in India rather than move to the US. This shift is due to the increasing opportunities and a robust startup ecosystem that India now offers.

“If I was graduating right now, I’m not sure I would come to the US”, said Adobe Narayen in an interview.

Education in India may not necessarily define attending college. Innovations in hiring practices reflect this transformation. Vishnu Vardhan, CEO of Vizzhy Inc., recently hired a Grade 9 student from Belgaum, emphasising talent over formal degrees.

Another example, Izam Mohammed, became an AI/ML engineer without attending college, acquiring skills through online resources. He developed a Python library for evaluating RAG models, securing a position in the industry at 18.

Some Quora and Reddit users believe the internet provides a lot of learning material to enhance AI skills. They argue that individuals can acquire knowledge virtually on any topic from the comfort of their homes.

While industry leaders like IBM’s Matthew Candy support this trend, stating that advancements in AI will democratise product creation, enabling individuals to innovate without extensive coding knowledge.

These examples indicate a broader acceptance of non-traditional education routes in India, signalling a shift in the country’s education and employment landscape.

Fine-Tuned Indic Llamas are ‘Utter Garbaggio’

It has been reiterated several times that the existing AI models from Google, Meta, and OpenAI are not inherently good when dealing with Indian language data, or any data in any language other than English. Worse is that even with expanding the models’ capabilities by showing Indic language data, the quality does not necessarily improve.

Raj Dabre, a prominent researcher at NICT in Kyoto, adjunct faculty at IIT Madras and a visiting professor at IIT Bombay, recently posted similar thoughts on X. “People be taking llama2, expanding vocabulary, pretraining on 2B tokens of a language and calling it a product,” he said, adding that he has already trained around 50 such models.

People be taking llama2, expanding vocabulary, pretraining on 2B tokens of a language and calling it a product. Bruh I have trained like 50 such models but I can tell you that outside of being useful to answer some research questions they are utter garbaggio.

— Raj Dabre (@prajdabre1) June 18, 2024

He further added that apart from answering some research questions, such models built on top of existing models, such as Mistral, Gemma, or Llama 2, are “utter garbaggio”.

Much of this is pointed towards the rise of open-source Indic language models such as Tamil Llama, Telugu Llama, Kannada Llama, and many such open-source offerings, which are built on top of open-source English language-based models.

This sentiment that India is not innovating in the AI space and merely building on top of existing models from the West has been echoed several times. When talking about India’s future in AI being bleak, several AI experts from India said that most LLMs produced in India are built on top of the already-available LLMs and cannot be called fundamental research.

Though there are others such as Pratik Desai from Kissan AI or Anubhav Sabharwal from CoRover.ai, who believe that building on top of existing open source models is good enough for making the models proprietary and building for specialised use cases.

Though startups like Sarvam AI are planning to build foundational models in Indic language, the current OpenHathi model is built on top of Meta’s Llama 2. Meanwhile, Soket AI Labs has already launched the Pragna-1B open source foundational model, but that is also yet to see a lot of adoption.

Much of this is because of the lack of adoption of Indic language models in the country. Even though everyone wants Indian models, the industry is not adopting them so readily.

Researchers are also content with fine-tuning with new languages on top of English-based models and trying them out for specific use cases as training a frontier foundational model would be a waste of resources for them.

The Creators Agree About the Adoption Problem

There is a widespread idea that open source is a good enough start for India as the adoption rate is too low. As Nandan Nilekani recently said that India’s focus should be on using AI to make a difference in people’s lives. “We are not in the arms race to build the next LLM, let people with capital, let people who want to pedal ships do all that stuff… We are here to make a difference, and our aim is to put this technology in the hands of people.”

Definitely, the factor of cost plays a big role, along with the flexibility of the open source models created by big-tech companies. When speaking with AIM, Adarsh Shirawalmath, the creator of Kannada Llama agreed that most of the problem within the country is that the industry is not willing to adopt the models created which are being built on top of existing models.

In a recent podcast with AIM, Arjun Rao, the founding partner of Speciale Invest, said that he would not be interested in investing in a company which is not doing foundational research and just building wrappers or models on top of existing open source offerings.

Earlier, in a conversation with AIM, Dabre also discussed the complexities of building models for Indic language. “These models [GPT-3] have seen close to tens of trillions of tokens or words in English. Unless you have seen the entirety of the web, or more or less all of it, none of these models will be able to actually solve the generative AI problem for that [Indian] language,” said Dabre.

Dabre rued that chatbots for Indian languages are still a dream. “You will see a lot of people claiming that they can make a chatbot or LLM for Indian languages, but 99% of those things are transient. They are not going to be too useful in production, because nobody has solved the data problem yet,” said Dabre. The biggest missing link here is the lack of Indic language data, which still needs to be solved.

For now, even though one can say that these fine-tuned models cannot be classified as products, they are ideal for research for students in universities. If companies such as Sarvam AI, Kissan AI, and Krutrim are still struggling to build foundational Indic language models, the individuals experimenting with such models should definitely be pushed further. Though not to be called products.

Reid Hoffman Believes AI Agents Will Soon Become Indispensable with Digital Twins

Reid Hoffman, co-founder of LinkedIn and a prominent venture capitalist, has expressed strong views on the future of AI, particularly the advent of AI agents in everyday life, during an interview with Washington Post Live.

He envisions a world where everyone will soon have AI agents to help them navigate the world while some people will choose to have digital twins, and it will be startling how soon this will happen.

When asked what’s possible or what’s plausible with AI 10 years from now, Hoffman candidly said, “This is the general way to look foolish when you make a specific claim 10 years in advance and then you know it’s never that way. The future is sooner and stranger. I think the most startling part about AI is that anyone who has a two-year vision out is either diluting themselves.”

Hoffman says that AI agents will revolutionise how we interact with technology, making it more intuitive and seamless. These agents, powered by advanced machine learning and natural language processing, will manage schedules, provide real-time information, and even offer emotional support.

Moreover, he also emphasises the potential of AI agents to drive innovation across multiple sectors, from healthcare to education. By handling mundane tasks, AI agents will free up human creativity and problem-solving capacities, fostering a new era of human-machine collaboration.

Reid Hoffman says everyone will soon have AI agents to help them navigate the world while some people will choose to have digital twins, and it will be startling how soon this will happen pic.twitter.com/etapZm70gP

— Tsarathustra (@tsarnick) June 18, 2024

Reid interviews his Digital Twin

In an interview aired back in April 24 of 2024, Reid Hoffman engaged with his digital self, an AI-generated avatar designed to emulate his thoughts and responses.

Why did I deepfake myself? To see if conversing with an AI-generated version of myself can lead to self-reflection, new insights into my thought patterns, and deep truths. pic.twitter.com/DWODoZ9lXL

— Reid Hoffman (@reidhoffman) April 24, 2024

This unique meet showcased the potential of AI to replicate human cognition and personality. Hoffman discussed various topics, including the future of AI, its ethical implications, and how digital selves could revolutionise personal and professional interactions.

The interview highlighted Hoffman’s belief in AI’s ability to augment human capabilities, emphasising that such technology can offer personalised assistance, streamline decision-making processes, and foster deeper understanding between humans and their digital counterparts.

Salesforce Announces Public Sector Division to Bring its CRM+AI to the Indian Government

Salesforce today announced the launch of its Public Sector division in India to drive transformation, aimed at empowering government agencies and public sector organisations to transform citizen experiences with Salesforce technology.

Salesforce Public Sector Solutions are designed to help government agencies serve people faster with out-of-the-box apps designed for digital service delivery.

Built leveraging the Salesforce Einstein 1 Platform, this allows government organisations to future proof their IT investment with citizen developer, AI, and automation tools, while helping to enhance their services’ agility, efficiency, and digital transformation.

Salesforce also recently announced the launch of Public Sector Einstein 1 for Service, including CRM, trusted AI, and data capabilities to help government agencies automate administrative tasks and provide faster service to citizens.

Salesforce Public Sector Solutions are available on a public cloud infrastructure, called Hyperforce, which is a next generation infrastructure architecture, built for the public cloud. This enables customers to help meet their data residency, data control and security obligations.

Fundamentally, Hyperforce is leveraging the power of public cloud infrastructure with a security-first culture, Zero Trust principles, and integration of enhanced privacy-centred standards. Salesforce’s product offerings enable government agencies and public sector organisations in India to succeed at scale.

Tableau and Einstein Analytics offer advanced data visualisation and AI-powered analytics. MuleSoft’s integration solutions make it easy to integrate Salesforce with any cloud or on-premises system to transform the experience.

Additionally, Slack makes work more productive and conversational with AI-powered summaries and data-triggered workflows. The Salesforce low code platform allows for creation of custom applications for unique needs. The AppExchange also offers a variety of pre-built apps specifically designed for government use.

“Our focus on the public sector, comes at a time when cloud has become the underlying strength of digital transformation efforts, playing a pivotal role in paving the way for innovation and propelling India to become a $1 trillion digital economy by 2030. Artificial intelligence – both predictive and generative, machine learning, and application development based on trust will boost citizen experiences,” Arundhati Bhattacharya, CEO & Chairperson, Salesforce India, said.

What Saurabh Netra’s Passion for Cricket Tells About Oracle’s Work Culture

A good work culture says a lot about the company. One such stellar example is that of Oracle, especially after Saurabh Netravalkar’s recent stint. His life extends beyond the cricket field, where he serves as senior executive at Oracle, perfectly juggling his responsibilities as a software engineer and a sportsman.

After Netravalkar architected United States of America’s (USA) unforgettable win over former champions Pakistan at the ICC World T20 2024, the Oracle techie’s LinkedIn profile became the talk of the town on social media. Netizens were quick to create and share memes highlighting Saurabh’s unique situation.

Being a software engineer at Oracle and getting Kohli out for a duck
Netravalkar is the coolest techbro ever. None of us stand a chance

— Saumil Heard It (@OnTheGrapevine) June 12, 2024

Oracle’s commitment to fostering a flexible and encouraging work environment, allowing him to excel in both fields has been highly appreciated. This support has provided the necessary resources and understanding to pursue his dual aspirations.

Netravalkar took to social media platform X, thanking his company for pursuing his dreams.

Thank you so much @Oracle for your support in enabling me to pursue my passion alongside my tech career! https://t.co/fEk3Or6CYZ

— Saurabh Netravalkar (@Saurabh_Netra) June 15, 2024

Netravalkar is not alone. Recently, Naveen Rao, VP of GenAI at Databricks, missed the Databricks AI + Data Summit 2024 because he was driving at Le Mans.

Tech X Sports

Apart from cricket, Oracle has also partnered with the Formula 1 Red Bull Racing team. The partnership allows Red Bull to leverage Oracle’s machine learning and data analytics capabilities on Oracle Cloud Infrastructure (OCI) to optimise data usage across their business operations, including car performance, race strategy, and fan engagement.

Indian tech companies are also becoming the go-to partners for sports federations and organisations around the world. The companies are using AI and analytics to help teams, partners, and other stakeholders to enhance the overall experience of their favourite sports.

Owing to its non-controversial and aspirational nature, sports provide a relatively safer platform in comparison. Overall, sports sponsorship in India witnessed ₹15,000 crore in 2023, up 10.95% from ₹14,209 crore a year ago, according to a report by ESP Properties, a division of GroupM.

Here are a few tech firms that are helping boost athletes.

Tech Mahindra, in 2020, partnered with Kings XI Punjab for digital fan engagement and contributed to the glitch-free 2014 FIFA World Cup by deploying hundreds of employees in Brazil and Hyderabad.

In June 2022, the company further boosted chess popularity in India by associating with the FIDE Women’s World Cup and FIDE Women’s Grand Prix, following a torch relay at its campuses.

Adani Group Chairman Gautam Adani expressed pride in supporting young chess prodigy Praggnanandhaa, commending his rapid progress and dedication to winning laurels for India. Praggnanandhaa thanked the Adani Group for their trust in his abilities and commitment to representing the nation.

A cricketer who knows how to code

Oracle fosters a diverse, inclusive culture valuing balance, teamwork, and personal growth, encouraging employees to pursue passions beyond work. This holistic approach sets a benchmark for other tech companies to create fulfilling work environments.

Netra’s cricket passion exemplifies Oracle’s work-life balance, demonstrating how personal fulfilment boosts professional performance.

This supportive environment is not exclusive to Netra. Oracle’s work culture is shaped by its appreciation for the diverse interests and talents of its employees, a philosophy reflected in the company’s broader approach. This culture is inspired by leaders like CEO Larry Ellison, who is known for his athletic pursuits in sailing.

Apart from Netravalkar, several other cricketers also had careers in technology before stepping onto the cricket field.

Dedication or Toxicity?

Recently, Saurabh Netravalkar’s sister Nidhi revealed that the US bowler carries his laptop and does office work from the hotels.

Speaking on CricketNext, Nidhi said, “He knows that when he’s not playing cricket, he has to give 100 per cent to the job. So right now, when he’s working, he carries his laptop everywhere. And he has the freedom to work from anywhere.”

“Even when he comes to India, he brings his laptop. He’s working. So after the match in the hotel, he’s doing his work. He is pretty dedicated like that.” she added.

Amidst this, came the disclosure about his professional life, internet users criticised Oracle for its detrimental work environment and denying him time off, aiming to maintain his concentration on the tournament. Meanwhile, others praised his dedication and commitment.

The revelation about the techie’s work-life balance sparked curiosity among people, leading them to speculate about his earnings both from his professional work and cricket. One such user on X had a question whether the star bowler would get paid time off from Oracle beyond 18 days?

Team USA may have qualified for the Super 8 of the Cricket World Cup for the first time in history…
but the real question is will their star bowler Netravalkar get paid time off from Oracle beyond 18 days? pic.twitter.com/ZV08rcrhXK

— Deedy (@deedydas) June 14, 2024

Although we might overestimate Saurabh’s cricket earnings, it is crucial to remember that his primary income source is most likely his demanding job at Oracle.

Apple now offers AI training for thousands of students and alumni

The rise of artificial intelligence has made it even more critical for employees to upskill, with a recent Microsoft study showing that 66% of leaders wouldn't hire someone without AI skills. Apple is trying to address that with its latest initiative.

On Tuesday, Apple announced that it will train thousands of Apple Developer Academy students, mentors, and alumni in "technologies and tools that take advantage of artificial intelligence (AI)" via a new core curriculum.

Also: 6 reasons why iOS 18 makes the iPhone 16 a must-upgrade for me

The custom-built curriculum will teach learners how to build, train, and deploy machine learning models across Apple's device ecosystem. Courses span the fundamentals of AI technologies and frameworks, CoreML, and more.

Students will learn through a guided curriculum and project-based assignments, with the assistance of hundreds of mentors and over 12,000 alumni, according to Apple. Starting this fall, Apple will offer the curriculum in 18 Developer Academies in six countries: Brazil, Indonesia, Italy, Saudi Arabia, South Korea, and the US.

"At Apple, we see coding as a universal language and believe in empowering developers, creators, and entrepreneurs across the world with tools and technologies that will allow them to create phenomenal experiences," Susan Prescott, Apple's VP of Worldwide Developer Relations, said in a statement.

Also: Here's every iPhone model that will support Apple's latest AI features (for now)

Students enrolled in the course will also have access to Apple's latest tools, including Xcode 16, the company's IDE for creating applications, and Swift Assist, a companion tool for coding tasks in Xcode 16. You can sign up for Apple Developer Academies for free.

This education push follows Apple's recent announcements at its Worldwide Developer's Conference, at which the company unveiled Apple Intelligence, its new "personal intelligence" system that infuses generative models throughout the Apple device ecosystem.

Now that Apple is all in on AI, it makes sense for the company to invest more into its developer community and train the next professionals to help carry its AI projects forward.

Artificial Intelligence

Bhavish Aggarwal Compares OpenAI to East India Company

In a recent conversation between Bhavish Aggarwal, CEO of Ola, and Vani Kola, founder and managing director of Kalaari Capital, Aggarwal gave an example of how India is exporting most of its digitized data to companies abroad such as OpenAI or Google, and they are selling it back to Indians, comparing it with what happened 200 years ago with the East India company.

“India generated about 20% of the world’s digitised data,” said Aggarwal, while also adding that only 10% of it is stored within the country. “90% of that is stored outside India.”

“The irony is that we create the data, but we don’t own the data. We don’t even store the data in our country,” Aggarwal continued, adding that India’s data is exported from the country into global data centres and processed for intelligence by OpenAI and others, and then sold back to us at a dollar rate.

He said that this sounds similar to how East India Company during the British rule of India used to operate with the textile and cotton industries. “Today is not a world for colonisation but this is exactly the same thing happening all over again,” Aggarwal added.

The problem that he notes is that India cannot run without Google or WhatsApp or any other product imported within the country. “It will topple the government,” he added.

However, Aggarwal believes that there’s a discontinuity with the advent of AI, where Indian companies can build something like Google or OpenAI and compete with the international market, which is also not sitting ducks. “But we have an opportunity,” said Aggarwal.

With AI, Aggarwal pointed out a problem that since AI would be pervise in our day-to-day lives, companies such as Meta or Google, can easily program people’s minds without even the need of a human creator.

This is similar to how the Ola chief was in the spotlight for weeks for saying that he does not want ‘pronoun illness’ to reach India, for which he received major backlash, but was also supported by many for the views.

Рубрика: AI