Manish Sharma is a Deputy News Editor at various esteemed publications. He specializes in themes such as AI and ML, retail, e-commerce, and healthcare, with a particular focus on regional interest and world news across the APAC region. Manish's work has been featured in prominent outlets including MyTravaly India, The Economic Times, and CNN-News18.
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Manish Sharma's coverage in local news, with a focus on crime, politics, and social issues within India (specifically Madhya Pradesh and Indore), suggests that he would be most responsive to pitches related to evolving stories or breaking news concerning these areas. Pitches should offer unique insights into ongoing events or present new angles on established topics.
Given his coverage of sensitive social issues such as crime and politics, Manish may respond well to expert commentary from individuals with direct experience or involvement in the matters being reported. He appears inclined towards covering contentious societal themes so ensure any pitch aligns with this approach.
Pitching relevant cultural events occurring locally in Madhya Pradesh or Indore could also resonate well with Manish since he covers culture & society extensively.
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Appointments strengthen product leadership in India and support AI-led innovation initiatives
In today's increasingly connected world of industrial manufacturing, IIoT options abound. Yet while having options is a good thing, too many options can make it difficult to identify the right technologies to meet an organization's unique circumstances.
You might have experienced this before. You visited a supermarket or browsed an online store, just to find something that is genuinely healthy and refreshing.
By: Manish Sharma, Gene Juknevicious, Todd Walden
AI is driving new computational demands at the industrial edge. Traditional GPUs compromise rugged industrial PC performance.
By: Manish Sharma
ABSTRACT Accurate depth determination for arbitrary shaped delamination remains a challenge in local defect resonance (LDR) testing methodology
Industrial AI requires compute closer to the process. Commercial servers are not designed for real-time OT needs.
Every CEO wants to talk about AI's magic. Almost none want to talk about the boring problems standing in the way. Recommended Video
For the past several years, artificial intelligence has largely been experienced through a screen. It answers questions, drafts text, writes code and generates images. The next phase will look very different. AI is beginning to move into the physical world. That means factories, rail systems, substations, warehouses, robots, buildings and other environments where software no longer simply advises a person, but increasingly interprets events, predicts outcomes and influences what happens next. Hitachi believes that shift will reshape the AI market, and it is deepening its relationship with NVIDIA around that conviction.
Many OT teams are overwhelmed by unstructured data. Data silos limit visibility and prevent actionable insights.
Operational excellence now requires continuous optimization, not just production output. Edge computing brings analytics and AI closer to the process.
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