Editorial 1. The ideal track to run India’s logistics system


The Union Budget 2023 has doubled the PM Gati Shakti National Master Plan (NMP) to States to ₹10,000 crore, and has announced an outlay of ₹2.4 lakh crore for the Indian Railways. The plan is a “transformative approach for economic growth and sustainable development dependent on the engines of roads, railways, airports, ports, mass transport, waterways and logistics infrastructure”.

Investing in Railways

The Railways offer an efficient and economic mode of logistics movement given their pan-India network, and can play an important role in enabling a coordinated and integrated logistics system.

With a target of increasing the share of the railways in freight movement from 27% to 45% and increasing freight movement from 1.2 billion tonnes to 3.3 billion tonnes, by 2030, PM Gati Shakti provides the right platform to address the infrastructural challenges that have hampered the movement of freight by rail.

Convenience over cost

Currently, the modal mix in terms of freight movement is skewed by a considerable extent towards road transport, with 65% of freight movement by road. The effect is an increased burden on roads, and, therefore, significant congestion, increased pollution, and resultant logistics cost escalations. The increased adoption of the railways as a mode for cargo movement is crucial to improve India’s logistics competitiveness.

A look at the comparable costs of different forms of transportation suggests that freight movement cost is the highest in the road sector — nearly twice the rail cost. However, the convenience of road transport has taken precedence over cost, and the railways in India have been losing freight share to other more flexible modes.

In 2020-21, share of the total freight movement :

  1. coal (44%)
  2. iron ore (13%)
  3. cement (10%)
  4. food grains (5%)
  5. fertilizers (4%)
  6. iron and steel (4%), etc.

Rise in container traffic

While the Indian Railways are upgrading their infrastructure (PM Gati Shakti National Master Plan), a continuous monitoring of existing projects along with identification of new priority areas will help in achieving the targets of rail freight movement. At present, these are significantly lower than other countries such as the United States and China.

The national transporter faces several infrastructural, operational and connectivity challenges, in turn leading to a shift of freight traffic to roads. The increased transit time by rail and pre-movement and post-movement procedural delays such as wagon placement, loading and unloading operations, multi-modal handling, etc., hamper freight movement by rail.

The lack of necessary terminal infrastructure, maintenance of good sheds and warehouses, and uncertain supply of wagons are some of the infrastructural challenges that customers face. This results in high network congestion, lower service levels, and increased transit time. The absence of integrated first and last-mile connectivity by rail increases the chances of damage due to multiple handling and also increases the inventory holding cost.

A special entity needed

The upcoming Dedicated Freight Corridors (DFCs) along India’s eastern and western corridors and multimodal logistics parks will ease the oversaturated line capacity constraints and improve the timing of trains. The Indian Railways need to improve infrastructure that is backed by adequate policy tools and also encourage private participation in the operation and management of terminals, containers, and warehouses to efficiently utilise resources.

Establishing a special entity under the railways to handle intermodal logistics in partnership with the private sector will help in addressing the first and last-mile issue faced by the railways. The entity could function as a single window for customers for cargo movement and payment transactions.

There are two cargo wagons in each passenger train. Based on industry recommendations, introduction of an Uber-like model for one of the two cargo wagons, wherein the customer can book the wagon using an online application, could help in increasing the utilisation rate of these wagons.

The Indian Railways may keep operating the other wagon, the way it is done currently, until the success of the proposed model is established. This could directly increase freight traffic without any additional investment in infrastructure.


An integrated logistics infrastructure with first and last-mile connectivity is essential to make rail movement competitive with roads, and facilitate exports by rail to neighbouring countries such as Nepal and Bangladesh.

Editorial 2. The future of Artificial Intelligence (AI)


Artificial Intelligence (AI) is the digital distillation of a technological revolution that is facilitating the long-overdue evolution of the human mind. AI, while disruptive and new, can trigger new avenues of intelligence in human minds. These new avenues can enable us to understand and attack society’s greatest challenges today.

About AI

Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by non-human animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs.

AI applications include advanced web search engines (e.g., Google Search), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Waymo), generative or creative tools (ChatGPT and AI art), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go).

Types of AI: AGI and ANI

What a layman does not know is that AI can traditionally be divided into Artificial General Intelligence (AGI) and Artificial Narrow Intelligence (ANI). AGI is designed to be capable of performing a wide variety of intellectual tasks, while ANI is designed to perform a single or a narrow set of related tasks.

AGI is designed to be flexible and adaptable, capable of handling new tasks and situations without human intervention. This which is often referred to as ‘unsupervised learning’ which means that the AI system can learn from data without being explicitly programmed to do so.

The difference between AGI and ANI lies in their scope of intelligence and their ability to generalise knowledge across different contexts. AGI is primarily driven by a variety of technical aspects that bear deeper discussion. One such aspect is the sophistication of AGI’s cognitive architecture — the development of a system that includes perception, attention, memory, language, and reasoning.

AGI is envisioned as having the ability to perform any intellectual task that a human can do, and to apply knowledge learned in one context to new, unfamiliar situations.

AGI is what you would consider the antagonist in pop-culture movies and lore where computers ‘take over’ civilisation and enslave humans. The fear emanates from the very real possibility that an AGI system continues to learn and make decisions that even its creators, I.e., us, cannot possibly predict. This lack of ‘control’ is what leads to the overarching fear of AI.

ANI, by contrast, is designed to perform a specific task or set of tasks and is not capable of generalising knowledge or skills to new situations outside of its programmed domain. Hence, it remains eminently controllable even if we do not fully understand the mechanics of how it gets so good at the task it is programmed for.

The future of jobs

ANI products like ChatGPT have existed for some time now but have recently taken the world by storm. Besides its technological prowess, it is also a matter of right place and right time. Other revolutionary technologies such as Q–Chat, Dall E-2, Synthesia are also on the rise to promote art and academia through fun and adaptive chat experiences.

ChatGPT is a chat bot (short for robot that can chat), which allows users to engage in a conversation about a variety of topics to which it like personal hobbies, interests, or current events and generates human-like responses in text form.

ChatGPT, and similar solutions, are particularly adept at automating routine and repetitive tasks, such as data entry and customer service, replacing acquisition teams administrative work, which could perhaps replace low-skill level workers. Many experts believe that AI will transform industries in significant ways, creating new opportunities for growth and innovation.

In industries like healthcare, for example, AI can optimise transportation networks, develop new materials, and even simplify manufacturing processes.

We can safely assume that AI can very well can lead to the displacement of some jobs. Buzzfeed layoffs were almost at the same time during its new deal with OpenAI to leverage ChatGPT for its articles. Many more industry veterans are on the cusp of an internal upheaval.

However, we should not forget that disruptive tech also creates new jobs and skill sets. AI may create demand for workers with expertise in machine learning, data science and natural language processing. and project management. It may also create opportunities for workers to specialise in areas where human judgement and creativity will remain critical.

The impact of AI on jobs and industries is likely to be uneven, with some workers and industries experiencing greater disruption than others. But this can be said for nearly every disruptive technology that was introduced in legacy business sectors. The printing press and the telephone transistors created vastly more opportunities in the long term.

In the case of AI, workers in low-wage and low-skill occupations may be more vulnerable to job loss than those in high-wage and high-skill occupations. But all is not lost. As AI continues to transform the job market, workers may need to acquire new skills and knowledge in order to remain employable. This could require significant investment in education and training programs, as well as new approaches to lifelong learning and skills development.


Overall, while there is still much uncertainty about the impact of AI on jobs and industries, it is evident that the technology is likely to have significant implications on the future of work. It will be important for policymakers, businesses, and workers to take proactive steps to manage this transition and ensure that the benefits of AI are shared widely across society.


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