TEHRAN (Iran News) Seyyed Sattar Hashemi, Minister of Communications and Information Technology, said at the National Conference on Investment Opportunities in ICT: “When we talk about the economy and digital transformation, it is no longer a choice but a strategic necessity.”

He added that the scale of investment required for digital economy infrastructure, and the multiplier effect it can generate, makes it clear that this sector stands apart from others in terms of returns and investment significance.

Hashemi stated that countries around the world are pursuing strategic approaches to investment in the digital economy, and Iran is doing the same. “At the Ministry of Communications—and in the country as a whole—we are focused on investment across various layers of the digital economy, with particular emphasis on incentivizing private-sector–led initiatives.”

Highlighting the legal framework outlined in the Seventh Development Plan, he noted that multiple provisions—especially in Chapter Thirteen—demonstrate the legislature’s strong attention to digital economic infrastructure and investment. “This indicates that Iran has taken an appropriate direction in addressing these needs from a regulatory standpoint,” he said.

Given the scale of investment required, the minister emphasized that it is neither feasible nor economically justified for the government alone to meet the country’s needs. “With a clear strategy and strong reliance on the private sector, the Ministry of Communications is opening the way for private investors across different layers of the digital economy.”

Hashemi reiterated the ministry’s focus on developing key communications infrastructure, including fiber-optic networks, 5G deployment, and readiness for future investment in 6G technologies.

He said that two main tracks are being pursued in fiber-optic development: an FTTH project led by private operators, and a national migration from copper to fiber led by Telecom Iran with the participation of other operators. Describing this as a major and lasting achievement, he noted that it marks a historic shift taking place during the current administration after nearly a century.

“Bold, wise, and forward-looking action is required,” Hashemi said, calling for the mobilization of all available capacities to seize the limited window of opportunity. “We hope, with collective effort, to take timely steps.”

He noted that with the long-awaited auction of 5G spectrum now completed, operators have entered the phase of building and equipping 5G infrastructure. But he emphasized that the core of any high-capacity communication network is data. “These infrastructures exist fundamentally to enable the flow of data.” “Artificial Intelligence”

Addressing the emerging need for national data management, Hashemi underscored the importance of data governance and data-centric development. “To achieve this, we must prioritize expanding storage infrastructure, data centers, and processing power.”

Within this framework, and based on mandates in high-level national plans, the government is moving to redevelop the national cloud platform with private-sector participation. Additionally, the Communications Regulatory Authority intends to issue licenses for AI operators, formally enabling private companies to operate AI services in the country. This initiative, he said, is rooted in the belief that progress in communications and data fields is impossible without the involvement of stakeholders and private industry.

Hashemi concluded by acknowledging existing challenges in the country’s data landscape and stressed the need for stronger collaboration with the private sector to overcome them.

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TEHRAN (Iran News) Artificial intelligence is like an engine with unprecedented power, yet we still do not know the exact roadmap, the final destination, or all the complexities of the journey. This is because AI grows very quickly and nonlinearly. Imagine you plant a seed expecting it to become an apple tree. But this seed grows so rapidly that every day it takes on a stranger shape. Today it looks like a tree, tomorrow like a building, and a week later something you have never seen before.

Progress in artificial intelligence is not linear (i.e., 1, 2, 3, 4…) but “exponential” (i.e., 2, 4, 8, 16…). The human mind has difficulty understanding the speed of exponential growth.

We Do Not Fully Understand “Intelligence”

We still do not correctly understand how human intelligence works. So how can we measure the path of an artificial “intelligence” that may have expectations and desires completely different from ours?

When an artificial intelligence surpasses human-level intelligence (this is referred to as the domain of Artificial General Intelligence, or AGI), it may begin to make changes and improvements on its own, beyond our comprehension and control. This point is called the technological singularity, and after it, all predictions become meaningless.

It should be noted that the path of artificial intelligence does not end with technology alone; it also depends on human decisions: ethics, economy, culture, and even traditions all take shape in a new context of integrated global data.

Think of it as if we have just discovered a new, unknown continent, knowing that it contains gold, diamonds, and miraculous medicines, but is also full of predatory animals and unknown diseases.

We cannot simply say, “Where does the journey to this new continent lead?” because the answer depends on who travels there, what rules are set, and how its dangers are confronted. Artificial intelligence is exactly the same—a digital, unknown continent. The future it brings is a combination of accumulated information from digital reserves, shaped by technology, and sometimes by human wisdom. Our task is to guide it as much as possible toward a defined future.

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TEHRAN (Iran News) – A team of scientists at Freie Universität Berlin has developed an artificial intelligence (AI) method for calculating the ground state of the Schrödinger equation in quantum chemistry. The goal of quantum chemistry is to predict the chemical and physical properties of molecules based solely on the arrangement of their atoms in space, avoiding the need for resource-intensive and time-consuming laboratory experiments. In principle, this can be achieved by solving the Schrödinger equation, but in practice, this is extremely difficult.

Up to now, it has been impossible to find an exact solution for arbitrary molecules that can be efficiently computed. But the team at Freie Universität has developed a deep learning method that can achieve an unprecedented combination of accuracy and computational efficiency. AI has transformed many technological and scientific areas, from computer vision to materials science. “We believe that our approach may significantly impact the future of quantum chemistry,” says Professor Frank Noé, who led the team effort. The results were published in the reputed journal Nature Chemistry.

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TEHRAN (Iran News) – AI, as a computer program, can identify breast cancer from routine scans with greater accuracy than human experts, researchers say in what they hope could prove a breakthrough in the fight against the global killer. 

Breast cancer is one of the most common cancers in women, with more than two million new diagnoses last year alone.

Regular screening is vital in detecting the earliest signs of the disease in patients who show no obvious symptoms.

In Britain, women over 50 are advised to get a mammogram every three years, the results of which are analyzed by two independent experts.

But interpreting the scans leaves room for error, and a small percentage of all mammograms either return a false positive — misdiagnosing a healthy patient as having cancer — or false-negative — missing the disease as it spreads.

Now researchers at Google Health have trained an artificial intelligence model to detect cancer in breast scans from thousands of women in Britain and the United States.

The images had already been reviewed by doctors in real life, but unlike in a clinical setting, the machine had no patient history to inform its diagnoses.

The team found that their AI model could predict breast cancer from the scans with a similar accuracy level to expert radiographers.

Further, the AI showed a reduction in the proportion of cases where cancer was incorrectly identified — 5.7 percent in the US and 1.2 percent in Britain, respectively.

It also reduced the percentage of missed diagnoses by 9.4 percent among US patients and by 2.7 percent in Britain.

“The earlier you identify a breast cancer the better it is for the patient,” Dominic King, UK lead at Google Health, told AFP.

“We think about this technology in a way that supports and enables an expert, or a patient ultimately, to get the best outcome from whatever diagnostics they’ve had.”

Computer ‘second opinion’

In Britain, all mammograms are reviewed by two radiologists, a necessary but labor-intensive process.

The team at Google Health also conducted experiments comparing the computer’s decision with that of the first human scan reader.

If the two diagnoses agreed, the case was marked as resolved. Only with discordant outcomes was the machine then asked to compare with the second reader’s decision.

The study by King and his team, published in Nature, showed that using AI to verify the first human expert reviewer’s cancer diagnosis could save up to 88 percent of the workload for the second clinician.

“Find me a country where you can find a nurse or doctor that isn’t busy,” said King.

“There’s the opportunity for this technology to support the existing excellent service of the (human) reviewers.”

Ken Young, a doctor who manages mammogram collection for Cancer Research UK, contributed to the study.

He said it was unique for its use of real-life cancer diagnosis scenarios from nearly 30,000 scans.

“We have a sample that is representative of all the women that might come through breast screening,” he said. “It includes easy cases, difficult cases and everything in between.”

The team said further research was needed, but they hoped that the technology could one day act as a “second opinion” for cancer diagnosis.

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Using Microsoft’s work at Northern Territory fisheries as an example, Hickin said the implementation of AI can “take away what we would call ‘grunt work’ in jobs and functions”.

The AI fisheries project uses the company’s Azure Cognitive Service to identify and count fish in waters without needing to sort through hours of under-water footage. The solution has already shown that the local golden snapper and black jewfish species are overfished.

“We’re seeing a lot of scientific work going on right now, where it uses huge amounts of data and it’s just impossible for a single person to assess that data and make the number of decisions they need to make … you can use AI to simplify the process to understand data, but you’re still using the scientists to make the final decision,” Hickin said.

Speaking alongside Hickin, Tech Research Asia founder and director Tim Dillion added that the use of AI in natural environments, such as the Northern Territory fisheries, can put humans in safer positions to do their jobs.

“The person who is undertaking the fish analysis, they are very attractive to a crocodile,” Dillon said.

“Processes such as this previously required divers to go into the harbour, so if you can remove a person from the environment and have the AI do that massive project, and to take that role out of danger and actually have that scientist doing the analysis and actually adding more value over the top, this is not a replacement of the role, it’s a change and an improvement.”

While the panel expressed great optimism around the potential of AI, Hickin said Australian companies have been slow to adopt such technologies. According to Hickin, the main reasons for the unwillingness to adopt AI are related to risk of failure, lack of trust, and lack of clarity of outcomes.

To implement AI, Hickin said, companies would have to ensure they have strong leadership groups that understand what business outcomes they wish to achieve out of using AI.

“In order to be successful, without a doubt, where we’ve seen the most success — whether it be AI, machine learning, or IoT — is when you have strong leadership that enables that ability for the organisation to understand, adapt, and take advantage of the technology,” Hickin said.

But with the rollout of 5G networks set to increase internet speeds by up to 20 times, Dillon expects the upcoming 5G backdrop will lead to an uptick of AI implementation by Australian companies.

According to Dillon, mining companies are already developing AI-based apps for mobile devices which combine the functions of cameras inside a mine, location tracking, and biometrics to alert companies whenever an employee is at the mine when they should not be. Once alerted, the company can send a notification to the unauthorised person’s mobile device to leave the mine and put on safety equipment.

Much like the AI fisheries project, Dillon said, the mining-based AI improves the safety of mining employees by ensuring they are always at the right place at the right time. He did note, however, that AI development is still very much in its early stages.

“It is spot-fires today because we’re in very early times, but if you look at what happened with 4G, the growth of what came through, this is game-changing,” Dillon said.

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