Avi Gopani is a technology journalist at Analytics India Magazine, known for her interdisciplinary approach to reporting. She specializes in examining industry trends and developments, particularly in the fields of artificial intelligence and data analytics. Her work not only covers the technical aspects of these evolving technologies but also delves into the cultural, political, and social narratives that intersect with technological progress.

Microsoft Build 2022 featured key announcements from CEO Satya Nadella, including new Azure features for cloud migration, Dev Box for developer project setups, Power Pages low code website builder, Azure Arc for hybrid environments, Azure Stack HCI for remote locations, Hybrid Loop for AI on cloud and edge, Azure OpenAI Service preview, GitHub Copilot general availability, Project Volterra development kit with Qualcomm, and Microsoft Intelligent Data Platform for unified data management. Microsoft Purview was also introduced for data governance and compliance.

SoftBank has divested from major tech stocks like Netflix and Facebook, as revealed in their Q2 holding report, contrasting their Q1 report. The company faced significant losses, particularly with its Vision Funds, but CEO Masayoshi Son remains optimistic about future investments in exponential technologies. The broader tech market is experiencing a downturn, with the Nasdaq index falling and tech giants freezing hiring. SoftBank's Vision Fund has seen both high returns and significant losses, notably with WeWork, Uber, and Didi IPOs. The company's SB Northstar venture and investments in Alibaba have also faced challenges. SoftBank is now focusing on the potential US IPO of ARM to recover from its losses.

Tesla reported a significant profit and emphasized the importance of lithium for the EV supply chain, hiring a geologist to explore mining options. Lithium prices have increased dramatically, and demand is expected to rise substantially by 2030. EV manufacturers are investing in lithium sources to shorten supply chains, with companies like General Motors, Volkswagen, and Tesla taking initiatives. The challenge lies in refining lithium at the required purity levels. Lithium's properties make it ideal for electric vehicle batteries, but the mining industry struggles to process metals to the necessary purity. Major lithium mines exist globally, with new regions expected to contribute to the supply. Managing the supply chain is crucial, with Tesla's mining efforts seen as a positive step.

Netflix introduced their Studio API and GraphQL Federation in 2020 to simplify the development of their API aggregation layer and to provide a unified API for consumers while allowing backend developers flexibility and service isolation. The federated GraphQL architecture enables independent building and operation of domain graph services under a unified schema. Netflix's Content Engineering has been transitioning to this platform, addressing the challenge of making a federated graph searchable. They developed Studio Search, using Elasticsearch to create a searchable subgraph of the federated graph. The architecture involves 'Change Data Capture' events, Netflix's CDC connectors, and a Data Mesh pipeline to ensure the index is up-to-date and scalable. Netflix's Studio applications produce events to Kafka streams, which are processed by Data Mesh processors and indexed into Elasticsearch.

Brian Kernighan reflects on the evolution of programming languages and computing over the past 50 years, from his early experiences with Fortran and time-sharing at MIT to the development of C and its enduring relevance. He discusses the trade-offs of using C, the challenges of updating the Linux Kernel's C code, and the advantages of languages like Python and Go. Kernighan also expresses skepticism about Web 3 and its associated technologies, questioning their necessity and environmental impact.

Mixture of Experts (MoE), a deep learning model architecture, is gaining popularity for its ability to scale AI models to trillion-plus parameters, enhancing capabilities in computer vision, speech recognition, natural language processing, and machine translation. Microsoft's Z-Code, an upgraded translator API, utilizes MoE to support multilingual capabilities and improve machine translation quality, even for underrepresented languages. Developed under Microsoft's AI at Scale and Turing initiatives, Z-Code has demonstrated performance gains in various language translations. Microsoft's collaboration with NVIDIA has optimized MoE model deployment on GPUs, achieving significant speedups and efficiency.

Souvik Ghosh, a third-year engineering student, has developed 'Sathi', a computer vision software designed to prevent harassment in public places. The system allows individuals to signal surveillance cameras using gestures, such as showing a fist or index finger, to trigger an alert to bystanders and notify the police. The prototype aims to automate the detection of harassment incidents in real-time, leveraging technology to enhance safety in metropolitan cities. Ghosh, who is also a student data scientist and social worker, was motivated by the prevalence of sexual harassment in India and the need for proactive measures. The system is still in the prototype stage, and Ghosh plans to refine it further with the help of industry experts and professors.

Google has introduced TRILLsson, a publicly available, on-device version of the CAP12 model, which is designed for paralinguistic speech recognition. TRILLsson is distilled from the 600M parameter CAP12 model, which was trained on the YT-U dataset consisting of over 900M hours of audio from YouTube videos. The CAP12 model excels in the NOSS Benchmark for Paralinguistic Tasks, particularly in emotion recognition. TRILLsson, despite being significantly smaller and trained on less data, performs comparably to CAP12. The research utilized knowledge distillation techniques such as global and local matching to train smaller, faster networks suitable for mobile devices. This advancement in paralinguistic speech models enhances speech recognition, text-to-speech production, and user intent interpretation.

Synthetic data's rising popularity is attributed to its ability to train AI models where real data is scarce or sensitive. Siemens Engineering Services in India and companies like Uber are using synthetic data for real-world applications. MIT Technology Review and Forrester have recognized its significance. NVIDIA's Omniverse Replicator exemplifies advancements in synthetic data generation. Despite its benefits, synthetic data's limitations include potential biases and the uncanny valley effect, which can impact the performance of AI models trained solely on synthetic data.

Icertis, a leading contract intelligence management company and India's second most valued SaaS unicorn, is transforming contract management with its AI-powered Icertis Contract Intelligence platform. Co-founded by Monish Darda and Samir Bodas in 2009, Icertis has pioneered cloud strategy in contract lifecycle management (CLM) and serves major firms like Google and Microsoft. The company's platform customizes solutions for different sectors without traditional customizations, using technical configurations instead. With recent Series F funding, Icertis plans to invest in sales, marketing, R&D, and geographical expansion, particularly in Japan and China. The metaverse is seen as a significant opportunity for the future of commerce and contract management.