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AstraZeneca has signed a deal worth up to $1.5 billion with biotechnology company Insitro to use artificial intelligence (AI) to discover new treatments for liver and heart diseases. Announced on October 15, 2026, the partnership will use Insitro’s “Virtual Human” AI platform to study diseases and identify potential targets for new drugs.

The research will focus on metabolic dysfunction-associated steatohepatitis (MASH), a serious form of fatty liver disease, and cardiomyopathies, which affect the heart muscle. The deal reflects growing interest in using AI to speed up drug discovery.

AstraZeneca will pay insitro $40 million upfront. Insitro could receive another $1.46 billion if the research meets specific development and sales targets. The deal also includes royalties on future drug sales, meaning the full $1.5 billion will depend on the programmes’ progress and commercial success.

What Is Insitro’s Virtual Human Platform?

Insitro’s Virtual Human platform uses artificial intelligence (AI), machine learning and lab-grown human cells to study how diseases develop. It combines biological data with computer-based analysis to help scientists understand the causes of diseases and identify possible targets for new drugs.

Finding the right drug target is an important step in drug discovery. It helps researchers identify which parts of the body or biological processes a new medicine should affect.

Under the AstraZeneca partnership, Insitro will use the platform to study MASH and cardiomyopathies. Researchers will investigate targets identified by AstraZeneca and work to turn promising findings into potential drug candidates.

The Virtual Human platform is not a complete digital copy of a person. It uses biological models, data and machine learning to study human diseases. Any potential findings will need further testing before they can support the development of new medicines.

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AstraZeneca Turns to AI to Find New Treatments for Liver and Heart Diseases

Developing new medicines can take years, partly because scientists need to understand what causes a disease and how to treat it. AI can help researchers analyse biological data and identify potential drug targets earlier in the research process.

AstraZeneca will use insitro’s AI platform to study MASH and heart muscle diseases. The aim is to identify biological targets that could help researchers develop new treatments for patients with these conditions.

The two companies will share the work. Insitro will use its AI technology and laboratory research to study diseases and identify potential drug candidates. AstraZeneca will handle clinical development and the later stages of bringing successful medicines to market.

The partnership combines Insitro’s expertise in AI and biological research with AstraZeneca’s experience in developing medicines. This could help researchers identify new treatment options for liver and heart diseases.

ALSO READ: AI Is Changing How Scientists Search for Treatments for Brain Diseases

AstraZeneca and Insitro Target Fatty Liver Disease and Heart Conditions

AstraZeneca and Insitro will use AI to identify potential drug targets for two conditions: metabolic dysfunction-associated steatohepatitis (MASH), a serious form of fatty liver disease, and cardiomyopathies, which affect the heart muscle.

MASH causes fat buildup, inflammation and liver damage. In severe cases, it can lead to cirrhosis or liver failure. The companies will use AI and human cell models to study the disease and identify possible targets for new treatments.

The research will also examine cardiomyopathies, which can affect the heart’s ability to pump blood and may lead to heart failure. The aim is to understand the biological causes of these conditions and identify potential drug candidates.

The research is still in its early stages. Any potential drugs will need further research and testing before they can be made available to patients.

How AstraZeneca’s $1.5 Billion AI Deal Could Shape Drug Discovery

The $1.5 billion AstraZeneca-insitro deal highlights the growing use of AI in drug discovery. The partnership combines AI analysis with laboratory research to help scientists understand diseases and identify potential targets for new medicines.

The agreement also shows that pharmaceutical companies are investing in biotechnology firms to support early-stage drug research. However, Insitro will receive most of the potential payments only if the research programmes meet specific development and commercial milestones.

The success of the partnership will depend on whether the research identifies promising drug targets and leads to potential treatments. Any resulting drug candidates will still need further development and testing.

The deal reflects AstraZeneca’s investment in AI-based drug discovery, but it remains uncertain whether the research will produce new medicines for liver and heart diseases.

The Group of Seven (G7) has agreed to run simulated AI cyberattacks. It will test how governments, central banks and financial regulators respond to cyber threats. The exercises will focus on protecting banks and key financial systems from attacks involving advanced artificial intelligence (AI).

The move follows a warning from the International Monetary Fund (IMF). The IMF said an AI-based cyberattack on a critical financial service could weaken public trust in financial institutions.

Japanese Finance Minister Satsuki Katayama confirmed the plan after a meeting of G7 finance ministers and central bank governors. The meeting took place alongside the IMF’s annual meetings in Bangkok, Thailand. Reuters reported the agreement on October 16, 2026.

G7 to Test Responses to AI Cyberattacks

The planned exercises will simulate cyberattacks involving advanced artificial intelligence (AI). They will help financial authorities test their emergency response plans and assess their readiness for such threats.

Officials will review the results to identify gaps in existing security measures. This might also lead to updates to response guidelines for handling AI-related cyberattacks. G7 financial authorities will develop the exercises. Private financial institutions may also take part, depending on the scenarios.

The G7 consists of Canada, France, Germany, Italy, Japan, the United Kingdom and the United States. The group works together on economic and financial issues affecting its members and the global economy.

Why AI Cyberattacks Are a Growing Threat to Banks

Banks and other financial institutions face new cybersecurity risks as AI systems become more advanced. Attackers could use AI to find software weaknesses, automate cyberattacks and carry out attacks faster.

These threats could affect banks, payment services and other critical financial systems. An attack on one institution could also spread through connected networks and disrupt services in multiple countries.

In a September 2025 statement on AI and cybersecurity, the G7 Cyber Expert Group warned about the risks of AI misuse. It said AI could increase the frequency and impact of cyberattacks. It also highlighted risks arising from financial institutions’ reliance on shared technology providers.

AI can also help banks detect security weaknesses, identify suspicious activity and respond to cyber incidents. However, financial authorities must prepare for attackers to use the same technology to target banks and critical financial systems.

ALSO READ: AI Cyber Attacks Statistics [2025 and beyond]

IMF Warns AI Cyberattacks Could Threaten Financial Stability

The International Monetary Fund (IMF) has warned that AI-related cyberattacks could pose risks to financial stability. An attack on a critical financial service could disrupt operations and weaken public trust in banks and other financial institutions.

The threat extends beyond individual banks. Financial institutions depend on connected networks, technology providers and payment systems. A major cyberattack could affect multiple institutions and disrupt financial markets at the same time.

The G7’s planned cyberattack simulations will test how authorities coordinate their response to such incidents. The exercises could help identify gaps in communication, crisis management and recovery plans before a real attack takes place.

ALSO READ: ARTEX AI Agent Pulled From GitHub After Cyberattacks Target South Korean Banks

G7 Strengthens Cybersecurity Measures Against AI Threats

The G7 is taking further steps to prepare banks and financial systems for new cyber threats. Regulators and central banks are assessing how advanced artificial intelligence (AI) could affect existing security measures and the ability of financial institutions to recover from major cyberattacks.

In July 2026, the G7 Cyber Expert Group announced that it had completed a cross-border exercise simulating a large-scale cyberattack across G7 countries. The exercise involved finance ministries, central banks, banking supervisors and financial market authorities. It tested how these agencies respond to cyber incidents, share information and communicate during a crisis.

The group also adopted a long-term plan to hold these exercises more regularly and follow a consistent approach. The upcoming AI cyberattack simulations will build on these efforts. They will test how financial authorities respond to cyber threats involving advanced AI systems.

How G7 Plans to Test Banks Against AI Cyberattacks

The planned G7 exercises could help governments and financial institutions find weaknesses in their cybersecurity plans and improve coordination during a crisis.

The tests will also help authorities assess whether current security measures can handle attacks involving advanced AI systems. However, their effectiveness will depend on the attack scenarios used. It will also depend on how officials use the findings to improve security.

The G7 has not yet shared a detailed schedule or confirmed which cyberattack scenarios the exercises will cover.

As AI technology advances, testing how financial systems respond to cyberattacks will become increasingly important. These tests can help protect banks, payment networks and the global economy.

Bank of America has hired 1,000 outside contractors to fix software security flaws found by advanced artificial intelligence (AI) models, including Anthropic’s Mythos. The move shows how AI tools can identify vulnerabilities faster than companies can fix them.

Bank of America CEO Brian Moynihan revealed the additional hiring in October 2026. The new contractors joined around 3,000 existing employees at the bank. Their work involves finding and fixing security flaws in Bank of America’s systems and third-party software.

The bank began hiring the contractors in the second quarter of 2026. They were still working with the company in October as Bank of America continued to address vulnerabilities identified by AI models.

Why Bank of America Hired 1,000 Contractors

Bank of America hired additional contractors after advanced AI models found software vulnerabilities that needed further checks and repairs. Anthropic’s Mythos can identify software flaws and assess how attackers could exploit them.

These AI capabilities can help security teams find weaknesses that traditional testing methods may miss. However, finding a vulnerability is only the first step. Teams must examine each issue, decide which ones need urgent attention and fix them without disrupting banking services.

Bank of America needed more technical staff to handle the growing workload. The 1,000 contractors are helping existing employees fix vulnerabilities in the bank’s software and applications developed by third-party vendors.

ALSO READ: AI Cyber Attacks Statistics [2025 and beyond]

Anthropic’s Mythos Raises Cybersecurity Concerns

Anthropic introduced Mythos in April 2026 with advanced capabilities to identify software vulnerabilities. The company limited access to the model because its ability to find and exploit security flaws could also create risks if attackers used it for cyberattacks.

Mythos can analyse software code, detect weaknesses and identify ways to exploit them. This creates a challenge for businesses that must fix security flaws before cybercriminals can take advantage of them.

To address these risks, Anthropic launched Project Glasswing. The initiative gives selected organisations access to its cybersecurity tools to help them find and fix weaknesses in critical software.

Banks face particular pressure to address these security risks. Financial institutions rely on complex IT systems and handle sensitive customer data. Any unpatched vulnerability could expose these systems to potential attacks.

Reuters reported in May 2026 that US banks were working to fix IT vulnerabilities identified by Mythos. This has raised questions about whether financial institutions could repair these weaknesses quickly enough. Advanced AI tools have made it easier to discover software flaws.

How AI-Detected Security Flaws Increase Cybersecurity Costs

Identifying software vulnerabilities is only the first step in cybersecurity. Once a flaw is identified, security teams must assess its severity, understand the risks and find a way to fix it.

The teams must then test the fixes to make sure they do not create new security problems or disrupt existing services. Large banks also need to coordinate repairs across their own systems and software supplied by external vendors.

This work can take significant time and resources, particularly when AI tools uncover large numbers of vulnerabilities across extensive amounts of code.

Bank of America’s decision to hire 1,000 contractors shows how large-scale AI security testing can increase the demand for technical staff. The additional workers are helping the bank investigate and fix vulnerabilities while its existing teams continue their work.

During discussions about the bank’s third-quarter results, CEO Brian Moynihan also addressed the costs involved in fixing these issues. However, the reported spending covered other areas, including anti-money-laundering matters. Therefore, it should not be treated as the confirmed cost of fixing vulnerabilities identified by AI models alone.

Bank of America Highlights the Challenges of AI Cybersecurity

Bank of America’s decision highlights a challenge facing businesses that use advanced AI cybersecurity tools. These tools can find software vulnerabilities quickly. But companies also need enough skilled workers and resources to fix the problems.

For banks, delays in fixing serious security flaws can increase the risk of cyberattacks, data leaks and service disruptions. Financial institutions may need to invest in automated security testing. They may also need to strengthen the teams responsible for fixing the vulnerabilities these tools uncover.

AI tools may eventually help security teams decide which vulnerabilities to fix first and automate some repairs. However, experts still need to test these fixes carefully. Mistakes in banking systems could affect customers and disrupt essential financial services.

ALSO READ: OpenAI Agent Accessed Non-Public Files on Australian Government Medicare Portal

Bank of America’s experience shows why companies must prepare for the workload created by advanced AI security tools. These tools can find software weaknesses faster. However, existing teams may struggle to fix all the problems they uncover.

As AI cybersecurity tools improve, businesses will need to strengthen their ability to identify and assess software vulnerabilities. They must also ensure they have enough staff to fix these issues.

CoreWeave’s falling shares and bond prices have raised questions about the money being used for AI. The company, backed by Nvidia, has around $50 billion in debt. Investors are concerned that its future earnings may not be enough to pay its bills and fund further growth.

On October 15, 2026, CoreWeave stock shares fell again, even as CEO Mike Intrator expressed confidence in the company’s customer contracts. Reuters reported that the stock had dropped more than 15% on Wednesday, followed by a further 6% decline in premarket trading on Thursday.

The company’s troubles also reflect a wider concern across the AI industry. Tech companies are spending billions on data centers, powerful chips and computing equipment. Some are borrowing heavily to pay for these investments.

Investors are now questioning whether the money earned from AI services will cover these costs. As borrowing becomes more expensive, companies face greater pressure to manage debt and show their investments can generate profits.

ALSO READ: AI Debt Issuance Falls to $23 Billion as Investors Reconsider the AI Boom

CoreWeave Faces Growing Concerns Over Its $50 Billion Debt

CoreWeave provides computing power to companies that develop and run AI models. To meet rising demand, it spends heavily on Nvidia chips, data centers, and other equipment. The company relies on borrowed money to fund much of this expansion, adding to its debt burden.

Investors are now questioning whether CoreWeave can manage its debt as spending continues to rise. Yields on its bonds due in 2031 have climbed above 16%, suggesting that investors see greater risks in lending to the company.

According to Reuters, the cost of insuring CoreWeave’s debt against default has also risen sharply. The latest figures indicated a nearly 63% chance of default within five years, compared with about 30% a year earlier.

Strong AI Demand Has Yet to Ease Concerns About CoreWeave’s Profits

CoreWeave’s financial troubles show that strong demand for AI services does not always lead to higher profits. Even when customers need more computing power, companies must manage the high costs of building and maintaining the infrastructure that supports them.

Analysts cited by Reuters expect CoreWeave to bring in nearly $13 billion in revenue in 2026. However, the company is also projected to post a loss of about $2.13 billion. Its spending plans have added to investor concerns. In August, CoreWeave raised its forecast for annual capital spending by $4 billion, putting the expected total at up to $39 billion.

The company needs this money to expand its data centers, purchase chips and meet the computing needs of its customers. These investments are necessary to support its business, but they also increase the amount of money it needs to raise.

This leaves CoreWeave facing a difficult balance. It must keep investing to meet growing demand, while managing its debt and controlling its costs.

Nvidia’s Support Gives CoreWeave Some Relief

CoreWeave has major customers, including Microsoft and OpenAI, and strong ties with Nvidia. According to Reuters, Nvidia has agreed to buy any computing capacity CoreWeave cannot sell to other customers through April 13, 2032.

CEO Mike Intrator told employees in a memo that CoreWeave’s customer contracts were worth more than its debt. Still, this does not mean CoreWeave is free from financial trouble. The company is also seeking an investment-grade credit rating, co-founder Brannin McBee told the Financial Times. A higher credit rating could make it easier for CoreWeave to borrow money.

Gartner Warns of Risks From Heavy AI Infrastructure Spending

CoreWeave’s financial troubles have added to concerns about whether revenue from AI services can justify the huge cost of building and running data centers. On October 15, Gartner warned that around 80% of specialised cloud providers, known as neoclouds, could shut down by 2030. The firm also said more than $3.5 trillion in AI infrastructure investments could lose value if companies fail to generate sufficient returns. 

Gartner expects AI infrastructure spending to reach nearly $1 trillion in 2026, followed by another $6 trillion between 2027 and 2030. Analyst Will Sommer warned that revenue from AI services may not be enough to make these investments profitable. If demand falls short of expectations, companies could struggle with expensive infrastructure and rising debt payments.

ALSO READ: AI Infrastructure Spending Statistics

AI Debt Concerns Spread Across Technology Stocks

CoreWeave stock price has raised concerns across the AI industry, affecting other companies investing heavily in AI infrastructure. Reuters reported that shares of rival cloud providers Nebius, Applied Digital and IREN fell between 3.2% and 5% on Thursday.

The wider tech sector has also suffered losses. The Philadelphia Semiconductor Index dropped 12% over six sessions, wiping out around $1.6 trillion in market value. The Nasdaq also fell more than 3% during the same period.

Investors are increasingly questioning the cost of the AI boom. Major US technology companies are expected to spend more than $700 billion on infrastructure in 2026, according to Reuters.

Companies such as Alphabet and Meta are also facing questions about the returns on their AI investments. Even businesses with strong finances could face pressure if spending continues to rise faster than revenue.

Whether you are an actor, musician, politician or an ordinary person, your face and voice are a part of your identity. However, AI tools have made it very easy for anyone to copy someone’s face and voice using just a couple of pictures and audio files. Through this, people can use deepfake content for advertisements, promotions, etc. Often, they do so without the person’s permission. This has raised consent and privacy issues.

Even if the content is not misleading or defamatory, using someone’s identity without their permission is still wrong. This has raised major questions for lawmakers: should your face and voice become the next form of digital property?

Denmark has recently introduced a bill against unauthorized use of people’s faces and voices. Even Italian Prime Minister Giorgia Meloni has trademarked her voice. Even though both cases have completely different legal approaches, it raises the same concern. 

Deepfakes Raise Questions About Identity and Consent

When it comes to deepfake laws, the main focus is often on the content itself. Whether the content is misleading, whether it involves any sort of fraud, etc. Although these are extremely important questions, deepfakes can still cause issues even when everyone is aware the content is fake. 

Unauthorized usage of someone’s appearance and voice raises consent and privacy issues. For example, imagine someone uses a popular actor’s face or voice to create an AI-generated video for an advertisement. The ad clearly states it was created using AI. Therefore, people will know the actor did not willingly appear for the advertisement. But the actor’s face and voice will still remain in the ad without their permission. 

Here the issue isn’t whether the advertisement is misleading or not. It’s more about whether someone has a right to use another person’s face and voice without their consent. 

This is why identity rights are important. A person’s face and voice are part of their identity and carry a financial value. Like, an actor earns money by appearing in films and advertisements. A musician earns money through their voice. Apart from celebrities, ordinary people also deserve to have control over how their face and voice are used. Therefore, deepfakes raise concerns about consent, privacy and financial loss. 

Denmark Is Moving Towards Stronger Likeness Rights

Denmark has suggested several changes into their copyright laws. This gives people more control over having their face or voice used without their permission. Denmark has introduced a bill that would ban people from sharing realistic deepfake content of people’s faces or voices without their permission. 

The proposed law in Denmark would give ordinary people and performers more protection against the unauthorised use of their faces, voices and performances in digital content. However, it’s important to know this law doesn’t restrict every use of AI content. 

Instead, it allows certain types of expression such as parody, cartoon, satire, and political or social criticism. However, it does have its limitations, as any content involving misinformation or serious risks would be restricted.

This bill is based on a political agreement made by Denmark’s previous government in June 2025. Culture Minister Zenia Stampe said the proposed law aims to address the growing ease of creating and sharing fake images and videos using AI.

ALSO READ: Denmark Moves to Ban AI Deepfakes Without Consent

Giorgia Meloni Has Filed for Trademarking Her Voice 

Italian Prime Minister Giorgia Meloni’s attempt to trademark her voice highlights the need to protect people from AI-generated voice copies.

Trademarks usually protect names, logos and other signs linked to a business or product. However, registering a voice as a trademark does not give someone full control over every recording or imitation of it. The protection depends on what is registered and how the law applies.

AI tools can copy a person’s voice and make it sound as if they said something they never actually said. Like, a fake recording could make Meloni appear to support a policy, make a controversial statement or promote a product. People might believe the recording is real before she has a chance to respond.

A trademark may help challenge some unauthorised uses of a voice, especially in advertising or other commercial activities. However, it may not cover every type of fake recording or political message.

Meloni’s case shows that existing laws may offer some protection against the misuse of AI-generated voices. But these laws have limits. Clearer rules may be needed to protect people’s voices and identities from being copied without their permission.

ALSO READ: Italy’s Meloni Tries to Trademark Her Voice Against AI Deepfakes

Should People Have Ownership Rights Over Their Faces and Voices?

Giving people more control over their faces and voices could help protect them from misuse. They could challenge others who use their identity without permission, especially when someone makes money from it.

It could also push businesses to ask for permission before using AI to copy a person’s face or voice. Companies that create virtual influencers, digital actors or AI advertisements would need to be clear about how they plan to use someone’s identity.

However, protecting a person’s identity is different from treating it like property that can be bought and sold.

A person’s face and voice are part of who they are. People should have a say in how they are used, even after signing a contract. Giving a company permission for one purpose should not mean it can use that person’s likeness however it wants.

For example, an actor might agree to let a film company create a digital copy of them for one movie. That should not give the company the right to use the same copy in advertisements or other films without asking again.

Contracts should clearly state how a person’s digital copy can be used and how long the permission lasts. They should also explain whether the company can change the copy or use it to train AI systems.

There is another concern. Stronger legal protection could be easier for celebrities and wealthy people to access because they can afford lawyers and court cases. Ordinary people who become victims of harmful deepfakes may not have the same resources.

Any new rules should make it easier for everyone to seek help and take action, regardless of their income or how well known they are.

AI Development Must Put Consent First

Technology companies should make consent an important part of how they create their AI tools. Companies need to consider how their products handle requests to copy someone’s voice or create a realistic digital version of a person.

Online platforms also have a role to play. They should make it easier for people to report content that uses their face or voice without permission. They should also handle impersonation complaints more effectively and provide clear information about whether content was created using AI.

Watermarks and content credentials can help people identify AI-generated content, but they cannot replace consent. Even if an AI-generated video is clearly labelled, it could still violate someone’s rights. Similarly, a real recording can be edited or combined with fake content to make it seem as though someone said or did something they never did.

Lawmakers, technology companies and online platforms will all need to address these problems. Each has a different role to play, and no single solution can prevent every form of misuse.

The Law Must Protect Identity Without Limiting Free Speech

Giving people stronger rights over their identity could help protect them from deepfakes. However, these laws must also protect freedom of speech.

Journalists may need to use a public figure’s voice when reporting on an issue. Filmmakers may create digital versions of real people for historical films. Comedians may imitate politicians, and artists may use AI-generated content to comment on social issues.

These cases should not be treated in the same way as fake advertisements or intimate deepfakes made without someone’s permission.

Lawmakers need to set clear rules about when these uses are allowed. They should consider why the content was created, how it is used and whether it could harm someone. At the same time, people should have a way to challenge the misuse of their identity. These laws should not allow powerful people to silence criticism or stop others from expressing their views.

The main goal should not be to give people complete control over every image, recording or discussion involving them. Instead, the law should prevent others from using their identity without permission in harmful or unfair ways while protecting free speech and creative work.

The Future of Deepfake Laws Depends on Identity Rights

The new bill introduced by Denmark and Giorgia Melon’s move to trademark her voice shows strong ways of protecting personal identity. Both cases point to a possible change in deepfake laws. Instead of focusing only on whether AI-generated content is false or misleading. Future laws should concentrate on giving people more control over how their faces and voices are used.

However, making these changes will require clear rules. Lawmakers must decide what counts as an unauthorised digital copy and when permission is needed. They must also protect the use of AI in journalism, art and public debate. Just as importantly, ordinary people should be able to take legal action when someone misuses their identity.

The main question is not whether people’s faces and voices should be treated as property that can be bought and sold. It is whether people should have a say in how AI uses their identity, especially when creating a digital copy has become so easy.